{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## License \n",
    "\n",
    "Copyright 2019-2020 Patrick Hall and the H2O.ai team\n",
    "\n",
    "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
    "you may not use this file except in compliance with the License.\n",
    "You may obtain a copy of the License at\n",
    "\n",
    "    http://www.apache.org/licenses/LICENSE-2.0\n",
    "\n",
    "Unless required by applicable law or agreed to in writing, software\n",
    "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
    "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
    "See the License for the specific language governing permissions and\n",
    "limitations under the License."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**DISCLAIMER:** This notebook is not legal compliance advice."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# All models are wrong ... but why is my model wrong?\n",
    "#### Part 1: Sensitivity analysis for model debugging"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\"All models are wrong but some are useful\" -- George Box, 1978"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook focuses on using sensitivity analysis to discover error mechanisms and security vulnerabilities and to assess stability and fairness in a trained XGBoost model. It begins by loading the UCI credit card default data and then training an interpretable, monotonically constrained XGBoost gradient boosting machine (GBM) model. (Pearson correlation with the prediction target is used to determine the direction of the monotonicity constraints for each input variable.) After the model is trained, global and local Shapley feature importance is calculated. These Shapley values help inform the application of partial dependence and ICE, and together these results guide a search for adversarial examples. The notebook closes by exposing the trained model to a _random attack_ and analyzing the attack results. These model debugging exercises uncover several accuracy, drift, and security problems such as over-emphasis of important features and non-robust interactions. Several remediation mechanisms are proposed including editing of final model artifacts, missing value injection or regularization during training, and use of assertions to inject missing values during scoring. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Python imports "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/patrickh/workspace/interpretable_machine_learning_with_python/env_iml/lib/python3.6/site-packages/sklearn/ensemble/weight_boosting.py:29: DeprecationWarning: numpy.core.umath_tests is an internal NumPy module and should not be imported. It will be removed in a future NumPy release.\n",
      "  from numpy.core.umath_tests import inner1d\n"
     ]
    }
   ],
   "source": [
    "import numpy as np                        # array, vector, matrix calculations\n",
    "import pandas as pd                       # DataFrame handling\n",
    "import shap                               # for consistent, signed variable importance measurements\n",
    "import xgboost as xgb                     # gradient boosting machines (GBMs)\n",
    "\n",
    "from itertools import combinations        # n choose k combinations of objects\n",
    "import string                             # for operations on character strings\n",
    "\n",
    "pd.options.display.max_columns = 999      # enable display of all DataFrame columns in notebook\n",
    "\n",
    "import matplotlib.pyplot as plt           # general plotting utilities\n",
    "from mpl_toolkits.mplot3d import Axes3D   # for 3-D projections\n",
    "from matplotlib import cm                 # colormaps for plots\n",
    "\n",
    "# enables display of plots in notebook\n",
    "%matplotlib inline\n",
    "\n",
    "np.random.seed(12345)                     # set random seed for global scope"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Download, explore, and prepare UCI credit card default data\n",
    "\n",
    "UCI credit card default data: https://archive.ics.uci.edu/ml/datasets/default+of+credit+card+clients\n",
    "\n",
    "The UCI credit card default data contains demographic and payment information about credit card customers in Taiwan in the year 2005. The dataset contains 23 input variables: \n",
    "\n",
    "* **`LIMIT_BAL`**: Amount of given credit (NT dollar)\n",
    "* **`SEX`**: 1 = male; 2 = female\n",
    "* **`EDUCATION`**: 1 = graduate school; 2 = university; 3 = high school; 4 = others \n",
    "* **`MARRIAGE`**: 1 = married; 2 = single; 3 = others\n",
    "* **`AGE`**: Age in years \n",
    "* **`PAY_0`, `PAY_2` - `PAY_6`**: History of past payment; `PAY_0` = the repayment status in September, 2005; `PAY_2` = the repayment status in August, 2005; ...; `PAY_6` = the repayment status in April, 2005. The measurement scale for the repayment status is: -1 = pay duly; 1 = payment delay for one month; 2 = payment delay for two months; ...; 8 = payment delay for eight months; 9 = payment delay for nine months and above. \n",
    "* **`BILL_AMT1` - `BILL_AMT6`**: Amount of bill statement (NT dollar). `BILL_AMT1` = amount of bill statement in September, 2005; `BILL_AMT2` = amount of bill statement in August, 2005; ...; `BILL_AMT6` = amount of bill statement in April, 2005. \n",
    "* **`PAY_AMT1` - `PAY_AMT6`**: Amount of previous payment (NT dollar). `PAY_AMT1` = amount paid in September, 2005; `PAY_AMT2` = amount paid in August, 2005; ...; `PAY_AMT6` = amount paid in April, 2005. \n",
    "\n",
    "These 23 input variables are used to predict the target variable, whether or not a customer defaulted on their credit card bill in late 2005. Because XGBoost accepts only numeric inputs, all variables will be treated as numeric."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Import data and clean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import XLS file\n",
    "path = 'default_of_credit_card_clients.xls'\n",
    "data = pd.read_excel(path,\n",
    "                     skiprows=1) # skip the first row of the spreadsheet\n",
    "\n",
    "# remove spaces from target column name \n",
    "data = data.rename(columns={'default payment next month': 'DEFAULT_NEXT_MONTH'}) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Assign modeling roles"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The shorthand name `y` is assigned to the prediction target. `X` is assigned to all other input variables in the credit card default data except the row identifier, `ID`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "y = DEFAULT_NEXT_MONTH\n",
      "X = ['LIMIT_BAL', 'SEX', 'EDUCATION', 'MARRIAGE', 'AGE', 'PAY_0', 'PAY_2', 'PAY_3', 'PAY_4', 'PAY_5', 'PAY_6', 'BILL_AMT1', 'BILL_AMT2', 'BILL_AMT3', 'BILL_AMT4', 'BILL_AMT5', 'BILL_AMT6', 'PAY_AMT1', 'PAY_AMT2', 'PAY_AMT3', 'PAY_AMT4', 'PAY_AMT5', 'PAY_AMT6']\n"
     ]
    }
   ],
   "source": [
    "# assign target and inputs for GBM\n",
    "y = 'DEFAULT_NEXT_MONTH'\n",
    "X = [name for name in data.columns if name not in [y, 'ID']]\n",
    "print('y =', y)\n",
    "print('X =', X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Display descriptive statistics\n",
    "The input variables `SEX`, `EDUCATION`, `MARRIAGE`, `PAY_0`-`PAY_6`, and the prediction target `DEFAULT_NEXT_MONTH`, are really categorical variables, but they have already been encoded into meaningful numeric, integer values, which is great for XGBoost. Also, there are no missing values in this dataset. \n",
    "\n",
    "(In a traditional credit scoring environment in the U.S., demographic variables like `SEX`, `EDUCATION`, `MARRIAGE` and `AGE` would not be used directly in the model, but only for disparate impact testing after model training. They are included in the model here for example purposes.) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <th>SEX</th>\n",
       "      <th>EDUCATION</th>\n",
       "      <th>MARRIAGE</th>\n",
       "      <th>AGE</th>\n",
       "      <th>PAY_0</th>\n",
       "      <th>PAY_2</th>\n",
       "      <th>PAY_3</th>\n",
       "      <th>PAY_4</th>\n",
       "      <th>PAY_5</th>\n",
       "      <th>PAY_6</th>\n",
       "      <th>BILL_AMT1</th>\n",
       "      <th>BILL_AMT2</th>\n",
       "      <th>BILL_AMT3</th>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <th>PAY_AMT6</th>\n",
       "      <th>DEFAULT_NEXT_MONTH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>3.000000e+04</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>3.000000e+04</td>\n",
       "      <td>30000.00000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "      <td>30000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>167484.322667</td>\n",
       "      <td>1.603733</td>\n",
       "      <td>1.853133</td>\n",
       "      <td>1.551867</td>\n",
       "      <td>35.485500</td>\n",
       "      <td>-0.016700</td>\n",
       "      <td>-0.133767</td>\n",
       "      <td>-0.166200</td>\n",
       "      <td>-0.220667</td>\n",
       "      <td>-0.266200</td>\n",
       "      <td>-0.291100</td>\n",
       "      <td>51223.330900</td>\n",
       "      <td>49179.075167</td>\n",
       "      <td>4.701315e+04</td>\n",
       "      <td>43262.948967</td>\n",
       "      <td>40311.400967</td>\n",
       "      <td>38871.760400</td>\n",
       "      <td>5663.580500</td>\n",
       "      <td>5.921163e+03</td>\n",
       "      <td>5225.68150</td>\n",
       "      <td>4826.076867</td>\n",
       "      <td>4799.387633</td>\n",
       "      <td>5215.502567</td>\n",
       "      <td>0.221200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>129747.661567</td>\n",
       "      <td>0.489129</td>\n",
       "      <td>0.790349</td>\n",
       "      <td>0.521970</td>\n",
       "      <td>9.217904</td>\n",
       "      <td>1.123802</td>\n",
       "      <td>1.197186</td>\n",
       "      <td>1.196868</td>\n",
       "      <td>1.169139</td>\n",
       "      <td>1.133187</td>\n",
       "      <td>1.149988</td>\n",
       "      <td>73635.860576</td>\n",
       "      <td>71173.768783</td>\n",
       "      <td>6.934939e+04</td>\n",
       "      <td>64332.856134</td>\n",
       "      <td>60797.155770</td>\n",
       "      <td>59554.107537</td>\n",
       "      <td>16563.280354</td>\n",
       "      <td>2.304087e+04</td>\n",
       "      <td>17606.96147</td>\n",
       "      <td>15666.159744</td>\n",
       "      <td>15278.305679</td>\n",
       "      <td>17777.465775</td>\n",
       "      <td>0.415062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>10000.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>-2.000000</td>\n",
       "      <td>-2.000000</td>\n",
       "      <td>-2.000000</td>\n",
       "      <td>-2.000000</td>\n",
       "      <td>-2.000000</td>\n",
       "      <td>-2.000000</td>\n",
       "      <td>-165580.000000</td>\n",
       "      <td>-69777.000000</td>\n",
       "      <td>-1.572640e+05</td>\n",
       "      <td>-170000.000000</td>\n",
       "      <td>-81334.000000</td>\n",
       "      <td>-339603.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>50000.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>3558.750000</td>\n",
       "      <td>2984.750000</td>\n",
       "      <td>2.666250e+03</td>\n",
       "      <td>2326.750000</td>\n",
       "      <td>1763.000000</td>\n",
       "      <td>1256.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>8.330000e+02</td>\n",
       "      <td>390.00000</td>\n",
       "      <td>296.000000</td>\n",
       "      <td>252.500000</td>\n",
       "      <td>117.750000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>140000.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>22381.500000</td>\n",
       "      <td>21200.000000</td>\n",
       "      <td>2.008850e+04</td>\n",
       "      <td>19052.000000</td>\n",
       "      <td>18104.500000</td>\n",
       "      <td>17071.000000</td>\n",
       "      <td>2100.000000</td>\n",
       "      <td>2.009000e+03</td>\n",
       "      <td>1800.00000</td>\n",
       "      <td>1500.000000</td>\n",
       "      <td>1500.000000</td>\n",
       "      <td>1500.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>240000.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>67091.000000</td>\n",
       "      <td>64006.250000</td>\n",
       "      <td>6.016475e+04</td>\n",
       "      <td>54506.000000</td>\n",
       "      <td>50190.500000</td>\n",
       "      <td>49198.250000</td>\n",
       "      <td>5006.000000</td>\n",
       "      <td>5.000000e+03</td>\n",
       "      <td>4505.00000</td>\n",
       "      <td>4013.250000</td>\n",
       "      <td>4031.500000</td>\n",
       "      <td>4000.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1000000.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>964511.000000</td>\n",
       "      <td>983931.000000</td>\n",
       "      <td>1.664089e+06</td>\n",
       "      <td>891586.000000</td>\n",
       "      <td>927171.000000</td>\n",
       "      <td>961664.000000</td>\n",
       "      <td>873552.000000</td>\n",
       "      <td>1.684259e+06</td>\n",
       "      <td>896040.00000</td>\n",
       "      <td>621000.000000</td>\n",
       "      <td>426529.000000</td>\n",
       "      <td>528666.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            LIMIT_BAL           SEX     EDUCATION      MARRIAGE           AGE  \\\n",
       "count    30000.000000  30000.000000  30000.000000  30000.000000  30000.000000   \n",
       "mean    167484.322667      1.603733      1.853133      1.551867     35.485500   \n",
       "std     129747.661567      0.489129      0.790349      0.521970      9.217904   \n",
       "min      10000.000000      1.000000      0.000000      0.000000     21.000000   \n",
       "25%      50000.000000      1.000000      1.000000      1.000000     28.000000   \n",
       "50%     140000.000000      2.000000      2.000000      2.000000     34.000000   \n",
       "75%     240000.000000      2.000000      2.000000      2.000000     41.000000   \n",
       "max    1000000.000000      2.000000      6.000000      3.000000     79.000000   \n",
       "\n",
       "              PAY_0         PAY_2         PAY_3         PAY_4         PAY_5  \\\n",
       "count  30000.000000  30000.000000  30000.000000  30000.000000  30000.000000   \n",
       "mean      -0.016700     -0.133767     -0.166200     -0.220667     -0.266200   \n",
       "std        1.123802      1.197186      1.196868      1.169139      1.133187   \n",
       "min       -2.000000     -2.000000     -2.000000     -2.000000     -2.000000   \n",
       "25%       -1.000000     -1.000000     -1.000000     -1.000000     -1.000000   \n",
       "50%        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "75%        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "max        8.000000      8.000000      8.000000      8.000000      8.000000   \n",
       "\n",
       "              PAY_6      BILL_AMT1      BILL_AMT2     BILL_AMT3  \\\n",
       "count  30000.000000   30000.000000   30000.000000  3.000000e+04   \n",
       "mean      -0.291100   51223.330900   49179.075167  4.701315e+04   \n",
       "std        1.149988   73635.860576   71173.768783  6.934939e+04   \n",
       "min       -2.000000 -165580.000000  -69777.000000 -1.572640e+05   \n",
       "25%       -1.000000    3558.750000    2984.750000  2.666250e+03   \n",
       "50%        0.000000   22381.500000   21200.000000  2.008850e+04   \n",
       "75%        0.000000   67091.000000   64006.250000  6.016475e+04   \n",
       "max        8.000000  964511.000000  983931.000000  1.664089e+06   \n",
       "\n",
       "           BILL_AMT4      BILL_AMT5      BILL_AMT6       PAY_AMT1  \\\n",
       "count   30000.000000   30000.000000   30000.000000   30000.000000   \n",
       "mean    43262.948967   40311.400967   38871.760400    5663.580500   \n",
       "std     64332.856134   60797.155770   59554.107537   16563.280354   \n",
       "min   -170000.000000  -81334.000000 -339603.000000       0.000000   \n",
       "25%      2326.750000    1763.000000    1256.000000    1000.000000   \n",
       "50%     19052.000000   18104.500000   17071.000000    2100.000000   \n",
       "75%     54506.000000   50190.500000   49198.250000    5006.000000   \n",
       "max    891586.000000  927171.000000  961664.000000  873552.000000   \n",
       "\n",
       "           PAY_AMT2      PAY_AMT3       PAY_AMT4       PAY_AMT5  \\\n",
       "count  3.000000e+04   30000.00000   30000.000000   30000.000000   \n",
       "mean   5.921163e+03    5225.68150    4826.076867    4799.387633   \n",
       "std    2.304087e+04   17606.96147   15666.159744   15278.305679   \n",
       "min    0.000000e+00       0.00000       0.000000       0.000000   \n",
       "25%    8.330000e+02     390.00000     296.000000     252.500000   \n",
       "50%    2.009000e+03    1800.00000    1500.000000    1500.000000   \n",
       "75%    5.000000e+03    4505.00000    4013.250000    4031.500000   \n",
       "max    1.684259e+06  896040.00000  621000.000000  426529.000000   \n",
       "\n",
       "            PAY_AMT6  DEFAULT_NEXT_MONTH  \n",
       "count   30000.000000        30000.000000  \n",
       "mean     5215.502567            0.221200  \n",
       "std     17777.465775            0.415062  \n",
       "min         0.000000            0.000000  \n",
       "25%       117.750000            0.000000  \n",
       "50%      1500.000000            0.000000  \n",
       "75%      4000.000000            0.000000  \n",
       "max    528666.000000            1.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[X + [y]].describe() # display descriptive statistics for all columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Investigate pair-wise Pearson correlations for `DEFAULT_NEXT_MONTH`\n",
    "\n",
    "Monotonic relationships are much easier to explain to colleagues, bosses, customers, and regulators than more complex, non-monotonic relationships and monotonic relationships may also prevent overfitting and excess error due to variance for new data.\n",
    "\n",
    "To train a transparent monotonic classifier, constraints must be supplied to XGBoost that determine whether the learned relationship between an input variable and the prediction target `DEFAULT_NEXT_MONTH` will be increasing for increases in an input variable or decreasing for increases in an input variable. Pearson correlation provides a linear measure of the direction of the relationship between each input variable and the target. If the pair-wise Pearson correlation between an input and `DEFAULT_NEXT_MONTH` is positive, it will be constrained to have an increasing relationship with the predictions for `DEFAULT_NEXT_MONTH`. If the pair-wise Pearson correlation is negative, the input will be constrained to have a decreasing relationship with the predictions for `DEFAULT_NEXT_MONTH`. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Calculate Pearson correlation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because `DEFAULT_NEXT_MONTH` is the last column in the `data` DataFrame, the last column of the Pearson correlation matrix indicates the direction of the linear relationship between each input variable and the prediction target, `DEFAULT_NEXT_MONTH`. According to the calculated values, as a customer's balance limit (`LIMIT_BAL`), bill amounts (`BILL_AMT1`-`BILL_AMT6`), and payment amounts (`PAY_AMT1`-`PAY_AMT6`) increase, their probability of default tends to decrease. However as a customer's number of late payments increase (`PAY_0`, `PAY_2`-`PAY6`), their probability of default usually increases. In general, the Pearson correlation values make sense, and they will be used to ensure that the modeled relationships will make sense as well. (Pearson correlation values between the target variable, DEFAULT_NEXT_MONTH, and each input variable are displayed directly below.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DEFAULT_NEXT_MONTH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <td>-0.153520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SEX</th>\n",
       "      <td>-0.039961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EDUCATION</th>\n",
       "      <td>0.028006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MARRIAGE</th>\n",
       "      <td>-0.024339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AGE</th>\n",
       "      <td>0.013890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_0</th>\n",
       "      <td>0.324794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_2</th>\n",
       "      <td>0.263551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_3</th>\n",
       "      <td>0.235253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_4</th>\n",
       "      <td>0.216614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_5</th>\n",
       "      <td>0.204149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_6</th>\n",
       "      <td>0.186866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT1</th>\n",
       "      <td>-0.019644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT2</th>\n",
       "      <td>-0.014193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT3</th>\n",
       "      <td>-0.014076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <td>-0.010156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <td>-0.006760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <td>-0.005372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <td>-0.072929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <td>-0.058579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <td>-0.056250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <td>-0.056827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <td>-0.055124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAY_AMT6</th>\n",
       "      <td>-0.053183</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           DEFAULT_NEXT_MONTH\n",
       "LIMIT_BAL           -0.153520\n",
       "SEX                 -0.039961\n",
       "EDUCATION            0.028006\n",
       "MARRIAGE            -0.024339\n",
       "AGE                  0.013890\n",
       "PAY_0                0.324794\n",
       "PAY_2                0.263551\n",
       "PAY_3                0.235253\n",
       "PAY_4                0.216614\n",
       "PAY_5                0.204149\n",
       "PAY_6                0.186866\n",
       "BILL_AMT1           -0.019644\n",
       "BILL_AMT2           -0.014193\n",
       "BILL_AMT3           -0.014076\n",
       "BILL_AMT4           -0.010156\n",
       "BILL_AMT5           -0.006760\n",
       "BILL_AMT6           -0.005372\n",
       "PAY_AMT1            -0.072929\n",
       "PAY_AMT2            -0.058579\n",
       "PAY_AMT3            -0.056250\n",
       "PAY_AMT4            -0.056827\n",
       "PAY_AMT5            -0.055124\n",
       "PAY_AMT6            -0.053183"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# displays last column of Pearson correlation matrix as Pandas DataFrame\n",
    "pd.DataFrame(data[X + [y]].corr()[y]).iloc[:-1] "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "#### Create tuple of monotonicity constraints from Pearson correlation values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The last column of the Pearson correlation matrix is transformed from a numeric column in a Pandas DataFrame into a Python tuple of `1`s and `-1`s that will be used to specify monotonicity constraints for each input variable in XGBoost. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# creates a tuple in which positive correlation values are assigned a 1\n",
    "# and negative correlation values are assigned a -1\n",
    "mono_constraints = tuple([int(i) for i in np.sign(data[X + [y]].corr()[y].values[:-1])])\n",
    "\n",
    "# (-1, -1, 1, -1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Split data into training and test sets for early stopping"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Train XGBoost with monotonicity constraints\n",
    "\n",
    "XGBoost is a very accurate, open source GBM library for regression and classification tasks. XGBoost can learn complex relationships between input variables and a target variable, but here the `monotone_constraints` tuning parameter is used to enforce monotonicity between inputs and the prediction for `DEFAULT_NEXT_MONTH`. XGBoost's early stopping functionality is also used to limit overfitting to the training data\n",
    "\n",
    "XGBoost is available from: https://github.com/dmlc/xgboost and the implementation of XGBoost is described in detail here: http://www.kdd.org/kdd2016/papers/files/rfp0697-chenAemb.pdf.\n",
    "\n",
    "After training, Shapley variable importance is calculated and displayed. Shapley values are an old idea, originally from the 1950s. A more recent innovation called _Tree SHAP_ made them more efficient for use in everyday data mining tasks: https://arxiv.org/pdf/1802.03888.pdf. Shapley variable importance is a global and local measure of the contribution of an input variable to the GBM model predictions. The global variable importance values give an indication of the magnitude of a variable's contribution to model predictions for all observations. To enhance trust in the GBM model, variable importance values should typically conform to human domain knowledge and reasonable expectations.\n",
    "\n",
    "\n",
    "**Note**: As of the h2o 3.24 \"Yates\" release, Shapley values and monotonicity constraints are supported in h2o. To see Shapley values and monotonicity constraints for an h2o GBM in action please see: https://github.com/jphall663/interpretable_machine_learning_with_python/blob/master/dia.ipynb."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The credit card default data is split into training and test sets to monitor and prevent overtraining. Reproducibility is another important factor in creating trustworthy models, and randomly splitting datasets can introduce randomness in model predictions and other results. A random seed was set above to ensure the data split is reproducible."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train data rows = 20946, columns = 25\n",
      "Test data rows = 9054, columns = 25\n"
     ]
    }
   ],
   "source": [
    "split_ratio = 0.70    # 70%/30% train/test split\n",
    "\n",
    "# execute split\n",
    "split = np.random.rand(len(data)) < split_ratio\n",
    "train = data[split]\n",
    "test = data[~split]\n",
    "\n",
    "# summarize split\n",
    "print('Train data rows = %d, columns = %d' % (train.shape[0], train.shape[1]))\n",
    "print('Test data rows = %d, columns = %d' % (test.shape[0], test.shape[1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Train XGBoost GBM classifier\n",
    "For brevity's sake, a previously-discovered set of good tuning parameters are specified here. Notice that the monotonicity constraints are passed to XGBoost using the `monotone_constraints` parameter. Because gradient boosting methods typically resample training data, an additional random seed is also specified for XGBoost using the `seed` parameter to create reproducible predictions, error rates, and variable importance values. To avoid overfitting, the `early_stopping_rounds` parameter is used to stop the training process after the test area under the curve (AUC) statistic fails to increase for 50 iterations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0]\ttrain-auc:0.738066\teval-auc:0.733449\n",
      "Multiple eval metrics have been passed: 'eval-auc' will be used for early stopping.\n",
      "\n",
      "Will train until eval-auc hasn't improved in 50 rounds.\n",
      "[1]\ttrain-auc:0.772991\teval-auc:0.769311\n",
      "[2]\ttrain-auc:0.775536\teval-auc:0.772624\n",
      "[3]\ttrain-auc:0.776248\teval-auc:0.771985\n",
      "[4]\ttrain-auc:0.777216\teval-auc:0.772796\n",
      "[5]\ttrain-auc:0.777782\teval-auc:0.773066\n",
      "[6]\ttrain-auc:0.777783\teval-auc:0.773471\n",
      "[7]\ttrain-auc:0.777856\teval-auc:0.773591\n",
      "[8]\ttrain-auc:0.777633\teval-auc:0.773209\n",
      "[9]\ttrain-auc:0.777417\teval-auc:0.772892\n",
      "[10]\ttrain-auc:0.777519\teval-auc:0.772666\n",
      "[11]\ttrain-auc:0.778476\teval-auc:0.773346\n",
      "[12]\ttrain-auc:0.778541\teval-auc:0.773312\n",
      "[13]\ttrain-auc:0.778351\teval-auc:0.773266\n",
      "[14]\ttrain-auc:0.778519\teval-auc:0.773695\n",
      "[15]\ttrain-auc:0.779383\teval-auc:0.774314\n",
      "[16]\ttrain-auc:0.779555\teval-auc:0.77473\n",
      "[17]\ttrain-auc:0.780178\teval-auc:0.775043\n",
      "[18]\ttrain-auc:0.780743\teval-auc:0.775246\n",
      "[19]\ttrain-auc:0.78146\teval-auc:0.776021\n",
      "[20]\ttrain-auc:0.781944\teval-auc:0.776477\n",
      "[21]\ttrain-auc:0.782181\teval-auc:0.776696\n",
      "[22]\ttrain-auc:0.782319\teval-auc:0.776915\n",
      "[23]\ttrain-auc:0.78263\teval-auc:0.776998\n",
      "[24]\ttrain-auc:0.782965\teval-auc:0.777144\n",
      "[25]\ttrain-auc:0.783396\teval-auc:0.777498\n",
      "[26]\ttrain-auc:0.783791\teval-auc:0.777791\n",
      "[27]\ttrain-auc:0.784151\teval-auc:0.778091\n",
      "[28]\ttrain-auc:0.784382\teval-auc:0.778375\n",
      "[29]\ttrain-auc:0.784678\teval-auc:0.778567\n",
      "[30]\ttrain-auc:0.784912\teval-auc:0.778755\n",
      "[31]\ttrain-auc:0.785231\teval-auc:0.778938\n",
      "[32]\ttrain-auc:0.785418\teval-auc:0.779125\n",
      "[33]\ttrain-auc:0.785598\teval-auc:0.779226\n",
      "[34]\ttrain-auc:0.785838\teval-auc:0.779421\n",
      "[35]\ttrain-auc:0.7861\teval-auc:0.779432\n",
      "[36]\ttrain-auc:0.786347\teval-auc:0.779549\n",
      "[37]\ttrain-auc:0.786633\teval-auc:0.779575\n",
      "[38]\ttrain-auc:0.786833\teval-auc:0.779668\n",
      "[39]\ttrain-auc:0.787093\teval-auc:0.779743\n",
      "[40]\ttrain-auc:0.787307\teval-auc:0.779926\n",
      "[41]\ttrain-auc:0.787602\teval-auc:0.780015\n",
      "[42]\ttrain-auc:0.787819\teval-auc:0.780089\n",
      "[43]\ttrain-auc:0.787943\teval-auc:0.780196\n",
      "[44]\ttrain-auc:0.788092\teval-auc:0.780239\n",
      "[45]\ttrain-auc:0.788194\teval-auc:0.780198\n",
      "[46]\ttrain-auc:0.788298\teval-auc:0.780235\n",
      "[47]\ttrain-auc:0.788422\teval-auc:0.780305\n",
      "[48]\ttrain-auc:0.78862\teval-auc:0.780372\n",
      "[49]\ttrain-auc:0.788803\teval-auc:0.780392\n",
      "[50]\ttrain-auc:0.789049\teval-auc:0.780558\n",
      "[51]\ttrain-auc:0.789221\teval-auc:0.780659\n",
      "[52]\ttrain-auc:0.789405\teval-auc:0.780756\n",
      "[53]\ttrain-auc:0.789553\teval-auc:0.780721\n",
      "[54]\ttrain-auc:0.78968\teval-auc:0.780791\n",
      "[55]\ttrain-auc:0.789779\teval-auc:0.780849\n",
      "[56]\ttrain-auc:0.789875\teval-auc:0.780932\n",
      "[57]\ttrain-auc:0.79002\teval-auc:0.780963\n",
      "[58]\ttrain-auc:0.790156\teval-auc:0.781038\n",
      "[59]\ttrain-auc:0.790292\teval-auc:0.781085\n",
      "[60]\ttrain-auc:0.790403\teval-auc:0.781079\n",
      "[61]\ttrain-auc:0.790509\teval-auc:0.781091\n",
      "[62]\ttrain-auc:0.790554\teval-auc:0.781061\n",
      "[63]\ttrain-auc:0.790635\teval-auc:0.781148\n",
      "[64]\ttrain-auc:0.790679\teval-auc:0.781166\n",
      "[65]\ttrain-auc:0.790822\teval-auc:0.781155\n",
      "[66]\ttrain-auc:0.790896\teval-auc:0.781178\n",
      "[67]\ttrain-auc:0.790977\teval-auc:0.781188\n",
      "[68]\ttrain-auc:0.791155\teval-auc:0.781211\n",
      "[69]\ttrain-auc:0.791239\teval-auc:0.781179\n",
      "[70]\ttrain-auc:0.7914\teval-auc:0.781347\n",
      "[71]\ttrain-auc:0.791525\teval-auc:0.78134\n",
      "[72]\ttrain-auc:0.791578\teval-auc:0.781312\n",
      "[73]\ttrain-auc:0.791691\teval-auc:0.781325\n",
      "[74]\ttrain-auc:0.791747\teval-auc:0.781323\n",
      "[75]\ttrain-auc:0.791801\teval-auc:0.781304\n",
      "[76]\ttrain-auc:0.791844\teval-auc:0.781313\n",
      "[77]\ttrain-auc:0.7919\teval-auc:0.781325\n",
      "[78]\ttrain-auc:0.792056\teval-auc:0.781448\n",
      "[79]\ttrain-auc:0.792088\teval-auc:0.781397\n",
      "[80]\ttrain-auc:0.792151\teval-auc:0.78138\n",
      "[81]\ttrain-auc:0.792173\teval-auc:0.781388\n",
      "[82]\ttrain-auc:0.792236\teval-auc:0.781301\n",
      "[83]\ttrain-auc:0.792327\teval-auc:0.781355\n",
      "[84]\ttrain-auc:0.792372\teval-auc:0.781356\n",
      "[85]\ttrain-auc:0.792402\teval-auc:0.781321\n",
      "[86]\ttrain-auc:0.79247\teval-auc:0.781286\n",
      "[87]\ttrain-auc:0.792521\teval-auc:0.781283\n",
      "[88]\ttrain-auc:0.792543\teval-auc:0.781265\n",
      "[89]\ttrain-auc:0.792595\teval-auc:0.781255\n",
      "[90]\ttrain-auc:0.792618\teval-auc:0.781242\n",
      "[91]\ttrain-auc:0.792673\teval-auc:0.781309\n",
      "[92]\ttrain-auc:0.792766\teval-auc:0.781357\n",
      "[93]\ttrain-auc:0.792826\teval-auc:0.781381\n",
      "[94]\ttrain-auc:0.792914\teval-auc:0.781387\n",
      "[95]\ttrain-auc:0.792967\teval-auc:0.781385\n",
      "[96]\ttrain-auc:0.793016\teval-auc:0.781375\n",
      "[97]\ttrain-auc:0.793053\teval-auc:0.781353\n",
      "[98]\ttrain-auc:0.79312\teval-auc:0.78137\n",
      "[99]\ttrain-auc:0.793145\teval-auc:0.781413\n",
      "[100]\ttrain-auc:0.793191\teval-auc:0.781456\n",
      "[101]\ttrain-auc:0.793256\teval-auc:0.781435\n",
      "[102]\ttrain-auc:0.793282\teval-auc:0.781382\n",
      "[103]\ttrain-auc:0.793322\teval-auc:0.781385\n",
      "[104]\ttrain-auc:0.793346\teval-auc:0.781361\n",
      "[105]\ttrain-auc:0.793399\teval-auc:0.781418\n",
      "[106]\ttrain-auc:0.793436\teval-auc:0.781398\n",
      "[107]\ttrain-auc:0.793511\teval-auc:0.781358\n",
      "[108]\ttrain-auc:0.793578\teval-auc:0.78137\n",
      "[109]\ttrain-auc:0.793655\teval-auc:0.781336\n",
      "[110]\ttrain-auc:0.793683\teval-auc:0.781299\n",
      "[111]\ttrain-auc:0.793701\teval-auc:0.781277\n",
      "[112]\ttrain-auc:0.79371\teval-auc:0.78128\n",
      "[113]\ttrain-auc:0.793745\teval-auc:0.781298\n",
      "[114]\ttrain-auc:0.793817\teval-auc:0.781307\n",
      "[115]\ttrain-auc:0.793838\teval-auc:0.781301\n",
      "[116]\ttrain-auc:0.793867\teval-auc:0.781308\n",
      "[117]\ttrain-auc:0.793877\teval-auc:0.781315\n",
      "[118]\ttrain-auc:0.793917\teval-auc:0.781246\n",
      "[119]\ttrain-auc:0.793947\teval-auc:0.781302\n",
      "[120]\ttrain-auc:0.794\teval-auc:0.781358\n",
      "[121]\ttrain-auc:0.794026\teval-auc:0.781357\n",
      "[122]\ttrain-auc:0.794053\teval-auc:0.781277\n",
      "[123]\ttrain-auc:0.794064\teval-auc:0.781257\n",
      "[124]\ttrain-auc:0.794209\teval-auc:0.781289\n",
      "[125]\ttrain-auc:0.794219\teval-auc:0.781288\n",
      "[126]\ttrain-auc:0.794287\teval-auc:0.781347\n",
      "[127]\ttrain-auc:0.79429\teval-auc:0.781347\n",
      "[128]\ttrain-auc:0.794327\teval-auc:0.781331\n",
      "[129]\ttrain-auc:0.794336\teval-auc:0.781349\n",
      "[130]\ttrain-auc:0.794367\teval-auc:0.781347\n",
      "[131]\ttrain-auc:0.794364\teval-auc:0.78134\n",
      "[132]\ttrain-auc:0.794385\teval-auc:0.781363\n",
      "[133]\ttrain-auc:0.794387\teval-auc:0.781326\n",
      "[134]\ttrain-auc:0.794472\teval-auc:0.78132\n",
      "[135]\ttrain-auc:0.794483\teval-auc:0.781326\n",
      "[136]\ttrain-auc:0.794495\teval-auc:0.781306\n",
      "[137]\ttrain-auc:0.794583\teval-auc:0.781293\n",
      "[138]\ttrain-auc:0.794589\teval-auc:0.781293\n",
      "[139]\ttrain-auc:0.7946\teval-auc:0.781286\n",
      "[140]\ttrain-auc:0.794642\teval-auc:0.7813\n",
      "[141]\ttrain-auc:0.794656\teval-auc:0.781303\n",
      "[142]\ttrain-auc:0.794654\teval-auc:0.781287\n",
      "[143]\ttrain-auc:0.794695\teval-auc:0.781273\n",
      "[144]\ttrain-auc:0.794705\teval-auc:0.781268\n",
      "[145]\ttrain-auc:0.794708\teval-auc:0.781268\n",
      "[146]\ttrain-auc:0.79471\teval-auc:0.781258\n",
      "[147]\ttrain-auc:0.794775\teval-auc:0.781284\n",
      "[148]\ttrain-auc:0.794782\teval-auc:0.781277\n",
      "[149]\ttrain-auc:0.794794\teval-auc:0.781283\n",
      "[150]\ttrain-auc:0.794815\teval-auc:0.78126\n",
      "Stopping. Best iteration:\n",
      "[100]\ttrain-auc:0.793191\teval-auc:0.781456\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# XGBoost uses SVMLight data structure, not Numpy arrays or Pandas DataFrames \n",
    "dtrain = xgb.DMatrix(train[X], train[y])\n",
    "dtest = xgb.DMatrix(test[X], test[y])\n",
    "\n",
    "# used to calibrate predictions to mean of y \n",
    "base_y = train[y].mean()\n",
    "\n",
    "# tuning parameters\n",
    "params = {\n",
    "    'objective': 'binary:logistic',             # produces 0-1 probabilities for binary classification\n",
    "    'booster': 'gbtree',                        # base learner will be decision tree\n",
    "    'eval_metric': 'auc',                       # stop training based on\n",
    "    'eta': 0.08,                                # learning rate\n",
    "    'subsample': 0.9,                           # use 90% of rows in each decision tree\n",
    "    'colsample_bytree': 0.9,                    # use 90% of columns in each decision tree\n",
    "    'max_depth': 15,                            # allow decision trees to grow to depth of 15\n",
    "    'monotone_constraints':mono_constraints,    # 1 = increasing relationship, -1 = decreasing relationship\n",
    "    'base_score': base_y,                       # calibrate predictions to mean of y \n",
    "    'seed': 12345                               # set random seed for reproducibility\n",
    "}\n",
    "\n",
    "# watchlist is used for early stopping\n",
    "watchlist = [(dtrain, 'train'), (dtest, 'eval')]\n",
    "\n",
    "# train model\n",
    "xgb_model = xgb.train(params,                   # set tuning parameters from above                   \n",
    "                      dtrain,                   # training data\n",
    "                      5000,                     # train up to 5000 iterations\n",
    "                      evals=watchlist,          # use watchlist for early stopping \n",
    "                      early_stopping_rounds=50, # stop after 50 rounds of no increase in AUC in test set \n",
    "                      verbose_eval=True)        # display iteration progress\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Global Shapley variable importance\n",
    "By setting `pred_contribs=True`, XGBoost's `predict()` function will return Shapley values for each row of the test set."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Calculate Shapley values using Tree SHAP\n",
    "Be sure to use the `ntree_limit=xgb_model.best_ntree_limit` option so that tree SHAP values are calculated for the best model. Also, the more trees, the slower the tree SHAP procedure! "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# dtest is DMatrix\n",
    "# shap_values is Numpy array\n",
    "shap_values = xgb_model.predict(dtest, pred_contribs=True, ntree_limit=xgb_model.best_ntree_limit)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Display Shapley values for each input variable\n",
    "Instead of relying on traditional single-value variable importance measures, local Shapley values for each input will be plotted below to get a more holistic and consistent measurement for the global importance of each input variable. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff712005c18>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# drop last column of Shapley value array, which is constant intercept\n",
    "# safest to use xgb_model.feature_names, seems to gaurantee consistent order\n",
    "shap.summary_plot(shap_values[:, :-1], test[xgb_model.feature_names])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the Shapley summary plot, it can be seen that `PAY_0`, or a customer's most recent repayment status, exerts a large influence on the model. High values of `PAY_0` are associated with large positive local contributions to model predictions. Low `PAY_0` values are associated with large negative local contributions to model predictions. `PAY_3`, or a customer's third most recent repayment status also seems to have a similar, but less intense, effect on the model predictions. `PAY_AMT1` and `PAY_AMT2`, a customer most and second-most recent payment amounts, display large negative local feature contributions. \n",
    "\n",
    "These results will be used to guide and inform model debugging by partial dependence, individual conditional expectation (ICE), and adversarial examples in the sections below."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4. Partial Dependence for Model Debugging\n",
    "\n",
    "Standard approaches for partial dependence and ICE are discussed at length in another notebook in this series: https://github.com/jphall663/interpretable_machine_learning_with_python/blob/master/xgboost_pdp_ice.ipynb. In general partial dependence is used to understand the average predictions of a model across the domain of one or more input variable(s). This alone is very helpful information from a model debugging perspective. A user can see generally when a model is making high predictions and low predictions and if this prediction behavior makes sense from an accuracy standpoint. You can also begin to understand the sensitivity of a model to any given input variable. If partial dependence swings widely across the domain of a given variable, the model predictions are likely sensitive to the values of this variable and this variable would be expected to have high importance in the model. \n",
    "\n",
    "Even if the model predictions are suitably accurate, being highly sensitive to the values of an input variable can present disparate impact, security, and stability problems. If a model's average predictions, as illustrated by partial dependence, are different across different races, genders, disability statuses, or other sensitive demographic attributes, this is likely cause for a deeper analysis into the observational fairness of the model's prediction behavior, such as a disparate impact analysis: https://github.com/jphall663/interpretable_machine_learning_with_python/blob/master/dia.ipynb.  Being highly sensitive to the values of any one input variable is also worrisome due to model drift and the ease with which an adversary could game the model predictions. Once a model is deployed, it's input variable values will likely drift as the real-world environment changes. Partial dependence can show us approximately how a model may react when drift occurs. If the model's simulated drift behavior is problematic, these drift patterns should be monitored closely after the model is deployed. The steps below will calculate partial dependence and ICE on missing values and high out-of-range values to test a model's performance on unseen data. Partial dependence can also be determined from public prediction APIs. A malicious actor can potentially see the same partial dependence plots as the model developers and use this information to construct adversarial examples to ensure they receive the prediction they want from the model. Adversarial examples are discussed further in Section 5. \n",
    "\n",
    "If a variable's partial dependence curve is mostly flat, the model should not be very sensitive to changes in the value of the variable and this variable would be expected to have low importance. If your model is placing high importance on a variable with a flat partial dependence curve, this could indicate a problem with your model training process, or the partial dependence itself could be misleading because the variable in question could be part of a group of strongly correlated variables or variables with strong interactions. ICE will be used to help increase the trustworthiness of partial dependence in the steps below. If the average global behavior of partial dependence is representative of the individual ICE curves, the partial dependence is likely trustworthy. If ICE curves diverge from partial dependence curves, this is an indication of strong correlation or interactions in the model training data which can cause accuracy problems in many cases. ICE also clues users into any local disparate impact, drift, or security problems: ICE can show if certain regions of the model's response function are overly sensitive to an individual's demographic segment or to any other changes in input variable values that may be interesting from a model drift or adversarial attack perspective. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Function for calculating partial dependence, its residuals, and ICE\n",
    "In addition to calculating partial dependence, the residuals of partial dependence can also be indicative of model error mechanisms in some cases. The function here can calculate partial dependence, it's residuals, and ICE."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def par_dep(xs, frame, model, y=None, resid=False, abs_=False, resolution=20,\n",
    "            bins=None):\n",
    "    \n",
    "    \"\"\" Calculates partial dependence and residuals of partial dependence.\n",
    "\n",
    "    Args:\n",
    "        xs: Variable for which to calculate partial dependence or its residuals.\n",
    "        frame: Pandas DataFrame for which to calculate partial dependence or \n",
    "               its residuals.\n",
    "        model: XGBoost model for which to calculate partial dependence or \n",
    "               its residuals.\n",
    "        y: Name of original target variable.   \n",
    "        resid: Return residuals of partial dependence instead of partial \n",
    "               dependence, default False.\n",
    "        abs_: Return unsigned, absolute residuals, default False.\n",
    "              (Good for handling both classes in logloss simultaneously.)\n",
    "        resolution: The number of points across the domain of xs for which \n",
    "                    to calculate partial dependence or its residuals, default 20.\n",
    "        bins: List of values at which to set xs, default 20 equally-spaced \n",
    "              points between column minimum and maximum.\n",
    "    \n",
    "    Returns: Pandas DataFrame containing partial dependence or its residual \n",
    "             values at bins.\n",
    "        \n",
    "    \"\"\"\n",
    "    \n",
    "    # turn off pesky Pandas copy warning\n",
    "    pd.options.mode.chained_assignment = None\n",
    "    \n",
    "    # initialize empty Pandas DataFrame with correct column names\n",
    "    return_frame = pd.DataFrame(columns=[xs,'residual'])\n",
    "    \n",
    "    # cache original column values \n",
    "    col_cache = frame.loc[:, xs].copy(deep=True)\n",
    "  \n",
    "    # determine values at which to calculate partial dependence\n",
    "    if bins == None:\n",
    "        min_ = frame[xs].min()\n",
    "        max_ = frame[xs].max()\n",
    "        by = (max_ - min_)/resolution\n",
    "        # modify max and by \n",
    "        # to preserve resolution and actually search up to max\n",
    "        bins = np.arange(min_, (max_ + by), (by + np.round((1. / resolution) * by, 3)))\n",
    "        \n",
    "    # residuals of partial dependence\n",
    "    if resid:        \n",
    "        \n",
    "        # initialize empty Pandas DataFrame with correct column names\n",
    "        return_frame = pd.DataFrame(columns=[xs,'residual'])\n",
    "        \n",
    "        for j in bins:\n",
    "\n",
    "            # frame to cache intermediate results\n",
    "            rframe_ = pd.DataFrame(columns=['actual', 'pred',  'res'])\n",
    "\n",
    "            frame.loc[:, xs] = j \n",
    "            dframe = xgb.DMatrix(frame.drop(y, axis=1)) \n",
    "            # reset index for expected merge behavior\n",
    "            rframe_['actual'] = frame[y].reset_index(drop=True)\n",
    "            rframe_['pred'] = pd.DataFrame(model.predict(dframe,\n",
    "                                                         ntree_limit=model.best_ntree_limit))\n",
    "            # logloss residual\n",
    "            rframe_['res'] = -rframe_['actual']*np.log(rframe_['pred']) -\\\n",
    "                             (1 - rframe_['actual'])*np.log(1 - rframe_['pred'])\n",
    "\n",
    "            if abs_:\n",
    "                # optionally return absolute value\n",
    "                resid_j = np.abs(rframe_['res']).mean() \n",
    "            else:\n",
    "                resid_j = rframe_['res'].mean()\n",
    "\n",
    "            del rframe_            \n",
    "\n",
    "            return_frame = return_frame.append({xs:j,\n",
    "                                               'residual': resid_j}, \n",
    "                                               ignore_index=True)\n",
    "            \n",
    "    # partial dependence  \n",
    "    else:   \n",
    "        \n",
    "        # initialize empty Pandas DataFrame with correct column names\n",
    "        return_frame = pd.DataFrame(columns=[xs, 'partial_dependence'])\n",
    "        \n",
    "        for j in bins:\n",
    "            frame.loc[:, xs] = j\n",
    "            dframe = xgb.DMatrix(frame)\n",
    "            par_dep_i = pd.DataFrame(model.predict(dframe, \n",
    "                                                   ntree_limit=model.best_ntree_limit))\n",
    "            par_dep_j = par_dep_i.mean()[0]\n",
    "            return_frame = return_frame.append({xs:j,\n",
    "                                               'partial_dependence': par_dep_j}, \n",
    "                                               ignore_index=True)\n",
    "           \n",
    "    # return input frame to original cached state    \n",
    "    frame.loc[:, xs] = col_cache\n",
    "\n",
    "    return return_frame\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Establish out-of-range and missing bins for partial dependence and ICE\n",
    "Users should consider how their models will behave in the future if their operating environment changes, such as in a recession, and then explicitly generate data to test their model behavior in these scenarios. Partial dependence, it's residuals, and ICE will be calculated for values in the training data, for missing values, and for values of `PAY_0` worse than those found in the training data, up to 10 months late on the most recent repayment. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "bins = [np.nan, -2.0, -1.5, -1.0, -0.5, 0.0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, 7.0, 7.5, 8.0, 8.5, 9.0, 9.5, 10.0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Calculate partial dependence and its residuals for the most important input variable in the GBM\n",
    "The table below includes partial dependence and it's residuals on missing and out-of-range data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PAY_0</th>\n",
       "      <th>partial_dependence</th>\n",
       "      <th>residual_0</th>\n",
       "      <th>residual_1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.165248</td>\n",
       "      <td>0.160465</td>\n",
       "      <td>1.581913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-2.0</td>\n",
       "      <td>0.165248</td>\n",
       "      <td>0.160465</td>\n",
       "      <td>1.581913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-1.5</td>\n",
       "      <td>0.175359</td>\n",
       "      <td>0.172128</td>\n",
       "      <td>1.522745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.175359</td>\n",
       "      <td>0.172128</td>\n",
       "      <td>1.522745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.5</td>\n",
       "      <td>0.175790</td>\n",
       "      <td>0.172634</td>\n",
       "      <td>1.519659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.175793</td>\n",
       "      <td>0.172638</td>\n",
       "      <td>1.519644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.5</td>\n",
       "      <td>0.261269</td>\n",
       "      <td>0.279674</td>\n",
       "      <td>1.136142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.261269</td>\n",
       "      <td>0.279674</td>\n",
       "      <td>1.136142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.5</td>\n",
       "      <td>0.556665</td>\n",
       "      <td>0.809080</td>\n",
       "      <td>0.484478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0.556665</td>\n",
       "      <td>0.809080</td>\n",
       "      <td>0.484478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2.5</td>\n",
       "      <td>0.556758</td>\n",
       "      <td>0.809351</td>\n",
       "      <td>0.484261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.556758</td>\n",
       "      <td>0.809351</td>\n",
       "      <td>0.484261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>3.5</td>\n",
       "      <td>0.556760</td>\n",
       "      <td>0.809355</td>\n",
       "      <td>0.484258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>4.0</td>\n",
       "      <td>0.556760</td>\n",
       "      <td>0.809355</td>\n",
       "      <td>0.484258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>4.5</td>\n",
       "      <td>0.556760</td>\n",
       "      <td>0.809355</td>\n",
       "      <td>0.484258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>5.0</td>\n",
       "      <td>0.556760</td>\n",
       "      <td>0.809355</td>\n",
       "      <td>0.484258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>5.5</td>\n",
       "      <td>0.556760</td>\n",
       "      <td>0.809355</td>\n",
       "      <td>0.484258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.556760</td>\n",
       "      <td>0.809355</td>\n",
       "      <td>0.484258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>6.5</td>\n",
       "      <td>0.556760</td>\n",
       "      <td>0.809355</td>\n",
       "      <td>0.484258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>7.0</td>\n",
       "      <td>0.556760</td>\n",
       "      <td>0.809355</td>\n",
       "      <td>0.484258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>7.5</td>\n",
       "      <td>0.556760</td>\n",
       "      <td>0.809355</td>\n",
       "      <td>0.484258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>8.0</td>\n",
       "      <td>0.556760</td>\n",
       "      <td>0.809355</td>\n",
       "      <td>0.484258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>8.5</td>\n",
       "      <td>0.556760</td>\n",
       "      <td>0.809355</td>\n",
       "      <td>0.484258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>9.0</td>\n",
       "      <td>0.556760</td>\n",
       "      <td>0.809355</td>\n",
       "      <td>0.484258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>9.5</td>\n",
       "      <td>0.556760</td>\n",
       "      <td>0.809355</td>\n",
       "      <td>0.484258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.556760</td>\n",
       "      <td>0.809355</td>\n",
       "      <td>0.484258</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    PAY_0  partial_dependence  residual_0  residual_1\n",
       "0     NaN            0.165248    0.160465    1.581913\n",
       "1    -2.0            0.165248    0.160465    1.581913\n",
       "2    -1.5            0.175359    0.172128    1.522745\n",
       "3    -1.0            0.175359    0.172128    1.522745\n",
       "4    -0.5            0.175790    0.172634    1.519659\n",
       "5     0.0            0.175793    0.172638    1.519644\n",
       "6     0.5            0.261269    0.279674    1.136142\n",
       "7     1.0            0.261269    0.279674    1.136142\n",
       "8     1.5            0.556665    0.809080    0.484478\n",
       "9     2.0            0.556665    0.809080    0.484478\n",
       "10    2.5            0.556758    0.809351    0.484261\n",
       "11    3.0            0.556758    0.809351    0.484261\n",
       "12    3.5            0.556760    0.809355    0.484258\n",
       "13    4.0            0.556760    0.809355    0.484258\n",
       "14    4.5            0.556760    0.809355    0.484258\n",
       "15    5.0            0.556760    0.809355    0.484258\n",
       "16    5.5            0.556760    0.809355    0.484258\n",
       "17    6.0            0.556760    0.809355    0.484258\n",
       "18    6.5            0.556760    0.809355    0.484258\n",
       "19    7.0            0.556760    0.809355    0.484258\n",
       "20    7.5            0.556760    0.809355    0.484258\n",
       "21    8.0            0.556760    0.809355    0.484258\n",
       "22    8.5            0.556760    0.809355    0.484258\n",
       "23    9.0            0.556760    0.809355    0.484258\n",
       "24    9.5            0.556760    0.809355    0.484258\n",
       "25   10.0            0.556760    0.809355    0.484258"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# calculate partial dependence\n",
    "par_dep_PAY_0 = par_dep('PAY_0', test[X], xgb_model, bins=bins)\n",
    "\n",
    "# calculate both classes of residuals on the same bins as above\n",
    "bins = list(par_dep_PAY_0['PAY_0'])\n",
    "\n",
    "# 0\n",
    "par_dep_PAY_0['residual_0'] = par_dep('PAY_0', test.loc[test[y] == 0, X + [y]], \n",
    "                                      xgb_model, y=y, resid=True, \n",
    "                                      bins=bins)['residual'] \n",
    "\n",
    "# 1\n",
    "par_dep_PAY_0['residual_1'] = par_dep('PAY_0', test.loc[test[y] == 1, X + [y]], \n",
    "                                      xgb_model, y=y, resid=True, \n",
    "                                      bins=bins)['residual'] \n",
    "\n",
    "par_dep_PAY_0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The expected monotonic behavior for `PAY_0` w.r.t. the model predictions holds even on missing data and out-of-range data. Although robust to missing values and high out-of-range values, this dependable behavior can make the model more susceptible to adversarial example attacks. Also, is the large swing in predicted probabilities w.r.t `PAY_0` justified or is the model over-emphasizing this input variable? These possibilities are analyzed in subsequent sections. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Helper function for finding percentiles of predictions\n",
    "\n",
    "ICE can be calculated for any row in the training or test data, but without intimate knowledge of a data source it can be difficult to know where to apply ICE. Calculating and analyzing ICE curves for every row of training and test data can be overwhelming, even for the example credit card default dataset. One place to start with ICE is to calculate ICE curves at every decile of predicted probabilities in a dataset, giving an indication of local prediction behavior across the dataset. The function below finds and returns the row indices for the maximum, minimum, and deciles of one column in terms of another."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_percentile_dict(sort_var, id_, frame):\n",
    "\n",
    "    \"\"\" Returns the percentiles of a column, sort_var, as the indices based on \n",
    "        another column id_.\n",
    "    \n",
    "    Args:\n",
    "        sort_var: Column in which to find percentiles.\n",
    "        id_: Row id, column that stores indices for percentiles of yhat.\n",
    "        frame: Pandas DataFrame containing sort_var and id_. \n",
    "    \n",
    "    Returns:\n",
    "        Dictionary of percentile values and index column values.\n",
    "    \n",
    "    \"\"\"\n",
    "    \n",
    "    # create a copy of frame and sort it by sort_var\n",
    "    sort_df = frame.copy(deep=True)\n",
    "    sort_df.sort_values(sort_var, inplace=True)\n",
    "    sort_df.reset_index(inplace=True)\n",
    "    \n",
    "    # find top and bottom percentiles\n",
    "    percentiles_dict = {}\n",
    "    percentiles_dict[0] = sort_df.loc[0, id_]\n",
    "    percentiles_dict[99] = sort_df.loc[sort_df.shape[0]-1, id_]\n",
    "\n",
    "    # find 10th-90th percentiles\n",
    "    inc = sort_df.shape[0]//10\n",
    "    for i in range(1, 10):\n",
    "        percentiles_dict[i * 10] = sort_df.loc[i * inc,  id_]\n",
    "\n",
    "    return percentiles_dict\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Find some percentiles of `p_DEFAULT_NEXT_MONTH`  in the test data\n",
    "The values for `ID` that correspond to the maximum, minimum, and deciles of predicted probability of default, or `p_DEFAULT_NEXT_MONTH`, are displayed below. ICE will be calculated for the rows of the test dataset associated with these `ID` values. Logloss residuals, or `r_DEFAULT_NEXT_MONTH` are also calculated here for use in Section 5."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: 23477,\n",
       " 99: 17757,\n",
       " 10: 6226,\n",
       " 20: 25603,\n",
       " 30: 12890,\n",
       " 40: 715,\n",
       " 50: 14517,\n",
       " 60: 4908,\n",
       " 70: 7411,\n",
       " 80: 6219,\n",
       " 90: 18421}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# merge GBM predictions and residuals onto test data\n",
    "yhat = 'p_DEFAULT_NEXT_MONTH'\n",
    "resid = 'r_DEFAULT_NEXT_MONTH' # residuals for use in section 5\n",
    "yhat_test = pd.concat([test.reset_index(drop=True), pd.DataFrame(xgb_model.predict(dtest, ntree_limit=xgb_model.best_ntree_limit))], axis=1)\n",
    "yhat_test = yhat_test.rename(columns={0: yhat})\n",
    "yhat_test[resid] = -yhat_test[y]*np.log(yhat_test[yhat]) -\\\n",
    "                             (1 - yhat_test[y])*np.log(1 - yhat_test[yhat]) # logloss\n",
    "\n",
    "# find percentiles of predictions\n",
    "yhat_percentile_dict = get_percentile_dict(yhat, 'ID', yhat_test)\n",
    "\n",
    "# display percentiles dictionary\n",
    "# ID values for rows\n",
    "# from lowest prediction \n",
    "# to highest prediction\n",
    "yhat_percentile_dict"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Calculate ICE curve values\n",
    "Here ICE curves are calculated at the minimum, maximum, and deciles of `p_DEFAULT_NEXT_MONTH`. In practice ICE should also be applied to understand **local** disparate impact, drift, and security concerns too. For example, it's reasonable to demand that changing any individual's demographic attributes should not greatly impact their prediction outcome. Additionally, ICE can uncover local, high sensitivity regions in the data or trained model response function. Perhaps a variable's average effect is negligible, but for certain high probability of default individuals, changing a variable value has a strong impact on model predictions. Or perhaps certain interactions only come into play for high probability of default individuals. ICE can be used to find a number of such locally interesting phenomena. ICE for `PAY_0` is calculated here, along with partial dependence and ICE for `AGE` -- which will be used in Section 5."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PAY_0</th>\n",
       "      <th>partial_dependence</th>\n",
       "      <th>residual_0</th>\n",
       "      <th>residual_1</th>\n",
       "      <th>Percentile_0</th>\n",
       "      <th>Percentile_10</th>\n",
       "      <th>Percentile_20</th>\n",
       "      <th>Percentile_30</th>\n",
       "      <th>Percentile_40</th>\n",
       "      <th>Percentile_50</th>\n",
       "      <th>Percentile_60</th>\n",
       "      <th>Percentile_70</th>\n",
       "      <th>Percentile_80</th>\n",
       "      <th>Percentile_90</th>\n",
       "      <th>Percentile_99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.165248</td>\n",
       "      <td>0.160465</td>\n",
       "      <td>1.581913</td>\n",
       "      <td>0.001872</td>\n",
       "      <td>0.057264</td>\n",
       "      <td>0.076212</td>\n",
       "      <td>0.097046</td>\n",
       "      <td>0.127956</td>\n",
       "      <td>0.142703</td>\n",
       "      <td>0.173241</td>\n",
       "      <td>0.222074</td>\n",
       "      <td>0.261528</td>\n",
       "      <td>0.151399</td>\n",
       "      <td>0.785043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-2.0</td>\n",
       "      <td>0.165248</td>\n",
       "      <td>0.160465</td>\n",
       "      <td>1.581913</td>\n",
       "      <td>0.001872</td>\n",
       "      <td>0.057264</td>\n",
       "      <td>0.076212</td>\n",
       "      <td>0.097046</td>\n",
       "      <td>0.127956</td>\n",
       "      <td>0.142703</td>\n",
       "      <td>0.173241</td>\n",
       "      <td>0.222074</td>\n",
       "      <td>0.261528</td>\n",
       "      <td>0.151399</td>\n",
       "      <td>0.785043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-1.5</td>\n",
       "      <td>0.175359</td>\n",
       "      <td>0.172128</td>\n",
       "      <td>1.522745</td>\n",
       "      <td>0.002067</td>\n",
       "      <td>0.061132</td>\n",
       "      <td>0.081262</td>\n",
       "      <td>0.102698</td>\n",
       "      <td>0.133810</td>\n",
       "      <td>0.153896</td>\n",
       "      <td>0.185654</td>\n",
       "      <td>0.236098</td>\n",
       "      <td>0.268033</td>\n",
       "      <td>0.162736</td>\n",
       "      <td>0.806465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.175359</td>\n",
       "      <td>0.172128</td>\n",
       "      <td>1.522745</td>\n",
       "      <td>0.002067</td>\n",
       "      <td>0.061132</td>\n",
       "      <td>0.081262</td>\n",
       "      <td>0.102698</td>\n",
       "      <td>0.133810</td>\n",
       "      <td>0.153896</td>\n",
       "      <td>0.185654</td>\n",
       "      <td>0.236098</td>\n",
       "      <td>0.268033</td>\n",
       "      <td>0.162736</td>\n",
       "      <td>0.806465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.5</td>\n",
       "      <td>0.175790</td>\n",
       "      <td>0.172634</td>\n",
       "      <td>1.519659</td>\n",
       "      <td>0.002302</td>\n",
       "      <td>0.061587</td>\n",
       "      <td>0.082731</td>\n",
       "      <td>0.102988</td>\n",
       "      <td>0.133810</td>\n",
       "      <td>0.153896</td>\n",
       "      <td>0.185654</td>\n",
       "      <td>0.236098</td>\n",
       "      <td>0.268033</td>\n",
       "      <td>0.163392</td>\n",
       "      <td>0.812470</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PAY_0  partial_dependence  residual_0  residual_1  Percentile_0  \\\n",
       "0    NaN            0.165248    0.160465    1.581913      0.001872   \n",
       "1   -2.0            0.165248    0.160465    1.581913      0.001872   \n",
       "2   -1.5            0.175359    0.172128    1.522745      0.002067   \n",
       "3   -1.0            0.175359    0.172128    1.522745      0.002067   \n",
       "4   -0.5            0.175790    0.172634    1.519659      0.002302   \n",
       "\n",
       "   Percentile_10  Percentile_20  Percentile_30  Percentile_40  Percentile_50  \\\n",
       "0       0.057264       0.076212       0.097046       0.127956       0.142703   \n",
       "1       0.057264       0.076212       0.097046       0.127956       0.142703   \n",
       "2       0.061132       0.081262       0.102698       0.133810       0.153896   \n",
       "3       0.061132       0.081262       0.102698       0.133810       0.153896   \n",
       "4       0.061587       0.082731       0.102988       0.133810       0.153896   \n",
       "\n",
       "   Percentile_60  Percentile_70  Percentile_80  Percentile_90  Percentile_99  \n",
       "0       0.173241       0.222074       0.261528       0.151399       0.785043  \n",
       "1       0.173241       0.222074       0.261528       0.151399       0.785043  \n",
       "2       0.185654       0.236098       0.268033       0.162736       0.806465  \n",
       "3       0.185654       0.236098       0.268033       0.162736       0.806465  \n",
       "4       0.185654       0.236098       0.268033       0.163392       0.812470  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# calculate partial dependence for AGE\n",
    "# (used later in section 5)\n",
    "# (interesting from disparate impact perspective)\n",
    "par_dep_AGE = par_dep('AGE', test[X], xgb_model) \n",
    "\n",
    "# retreive bins from partial dependence calculation\n",
    "bins_PAY_0 = list(par_dep_PAY_0['PAY_0']) \n",
    "bins_AGE = list(par_dep_AGE['AGE']) \n",
    "\n",
    "# for each percentile in percentile_dict\n",
    "# create a new column in the par_dep frame \n",
    "# representing the ICE curve for that percentile\n",
    "# and the variables of interest, PAY_0 and AGE\n",
    "for i in sorted(yhat_percentile_dict.keys()):\n",
    "    \n",
    "    col_name = 'Percentile_' + str(i)\n",
    "    \n",
    "    # ICE curves for PAY_0 across percentiles at bins_PAY_0 intervals\n",
    "    par_dep_PAY_0[col_name] = par_dep('PAY_0', \n",
    "                                    test[test['ID'] == int(yhat_percentile_dict[i])][X],  \n",
    "                                    xgb_model, \n",
    "                                    bins=bins_PAY_0)['partial_dependence']\n",
    "    \n",
    "    # ICE curves for AGE across percentiles at bins_AGE intervals\n",
    "    par_dep_AGE[col_name] = par_dep('AGE', \n",
    "                            test[test['ID'] == int(yhat_percentile_dict[i])][X],  \n",
    "                            xgb_model, \n",
    "                            bins=bins_AGE)['partial_dependence']\n",
    "    \n",
    "\n",
    "par_dep_PAY_0.head(n=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Helper function to plot partial dependence and ICE\n",
    "\n",
    "Overlaying partial dependence onto ICE in a plot is a convenient way to validate and understand both global and local monotonic behavior, even on out-of-range and missing data. Plots of partial dependence curves overlaid onto ICE curves for several percentiles of predictions for `DEFAULT_NEXT_MONTH` are used to validate monotonic behavior on missing and out-of-range data, describe the GBM model mechanisms, and to compare the local GBM behavior with the average GBM behavior in the test data to determine the trustworthiness of partial dependence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_par_dep_ICE(xs, par_dep_frame, ax=None, ticks=None, labels=None):\n",
    "\n",
    "    \n",
    "    \"\"\" Plots ICE overlayed onto partial dependence for a single variable.\n",
    "    Conditionally uses user-defined axes, ticks, and labels for grouped subplots.\n",
    "    \n",
    "    Args: \n",
    "        xs: Name of variable for which to plot ICE and partial dependence.\n",
    "        par_dep_frame: Name of Pandas DataFrame containing ICE and partial\n",
    "                       dependence values.\n",
    "        ax: Matplotlib axis object to use, default None.         \n",
    "        ticks: List of numeric x-axis tick marks, default None.  \n",
    "        labels: List of string values to use as the visual label for ticks, \n",
    "                default None. \n",
    "    \n",
    "    \"\"\"\n",
    "    \n",
    "    # initialize figure and axis for grouped subplots \n",
    "    if (ticks is None) & (labels is None) & (ax is None):\n",
    "        pass\n",
    "    else:\n",
    "        _ = ax.set(xticks=ticks, xticklabels=labels) # user-defined \n",
    "    \n",
    "    # for standalone plotting\n",
    "    if ax is None:\n",
    "        \n",
    "        # initialize figure and axis\n",
    "        fig, ax = plt.subplots()\n",
    "        \n",
    "        # plot ICE\n",
    "        par_dep_frame.drop('partial_dependence', axis=1).plot(x=xs, \n",
    "                                                              colormap='coolwarm', \n",
    "                                                              ax=ax)\n",
    "        # overlay partial dependence, annotate plot\n",
    "        par_dep_frame.plot(title='Partial Dependence with ICE',\n",
    "                           x=xs, \n",
    "                           y='partial_dependence',\n",
    "                           color='grey', \n",
    "                           linewidth=3, \n",
    "                           ax=ax)\n",
    "    \n",
    "    # for grouped subplots \n",
    "    else: \n",
    "        \n",
    "        # plot ICE\n",
    "        par_dep_frame.drop('partial_dependence', axis=1).plot(x=xs, \n",
    "                                                              colormap='coolwarm',\n",
    "                                                              ax=ax)\n",
    "        # overlay partial dependence, annotate plot\n",
    "        par_dep_frame.plot(title='Partial Dependence with ICE',\n",
    "                           x=xs, \n",
    "                           y='partial_dependence',\n",
    "                           color='grey', \n",
    "                           linewidth=3, \n",
    "                           ax=ax)\n",
    "\n",
    "    # add legend\n",
    "    _ = plt.legend(bbox_to_anchor=(1.05, 0),\n",
    "                   loc=3, \n",
    "                   borderaxespad=0.)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot partial dependence, its residuals, and ICE along with a histogram of `PAY_0` grouped by target class\n",
    "Another aspect of determining the trustworthiness of partial dependence and ICE is understanding the amount of data available for the model to learn from in different local regions. For _any_ valid input data schema and values, a model will generate a prediction. This does not mean the model learned anything meaningful about that new kind of input data during training. To look for any possible *epistemic uncertainty* issues, a histogram is plotted alongside partial dependence, it's residuals, and ICE. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff712400c88>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# setup ########################################################################\n",
    "\n",
    "# tricks to have NaN appear on the x-axis\n",
    "par_dep_PAY_0.iloc[0, 0] = -2.5\n",
    "ticks = [-2.5] + list(par_dep_PAY_0['PAY_0'])[2:][::3]\n",
    "labels = ['NaN'] + list(par_dep_PAY_0['PAY_0'])[2:][::3]\n",
    "\n",
    "# setup 3-way figure\n",
    "fig, (ax0, ax1, ax2) = plt.subplots(ncols=3, sharey=False)\n",
    "plt.tight_layout()\n",
    "plt.subplots_adjust(left=0.0, right=2.5, wspace=0.2)\n",
    "   \n",
    "# histogram grouped by target class for PAY_0 ##################################\n",
    "\n",
    "from matplotlib.lines import Line2D # custom legend\n",
    "custom_lines = [Line2D([0], [0], color='royalblue', lw=4),\n",
    "                Line2D([0], [0], color='deeppink', lw=4)]\n",
    "\n",
    "# establish groups and plot w/ custom legend\n",
    "gb = test.groupby(['PAY_0', y]).count()\n",
    "gb['color'] = 'deeppink'\n",
    "gb.iloc[::2, :]['color'] = 'royalblue'\n",
    "_ = test.groupby(['PAY_0', y]).count().plot(kind='bar', y='ID', legend=False, \n",
    "                                            color=gb['color'], \n",
    "                                            title='Distribution of DEFAULT_NEXT_MONTH by PAY_0', \n",
    "                                            ax=ax0)\n",
    "_ = ax0.legend(custom_lines, ['PAY_0: 0', 'PAY_0: 1'])\n",
    " \n",
    "# partial dependence and residuals #############################################\n",
    "\n",
    "_ = ax1.set(xticks=ticks, xticklabels=labels)\n",
    "_ = par_dep_PAY_0.plot(kind='line', x='PAY_0', y='partial_dependence', \n",
    "                       color='darkgrey', linewidth=3,\n",
    "                       title='Partial Dependence with LogLoss Residuals', \n",
    "                       ax=ax1)\n",
    "_ = par_dep_PAY_0.plot(kind='line', x='PAY_0', y='residual_0', color='royalblue', \n",
    "                       linestyle='--', ax=ax1)\n",
    "_ = par_dep_PAY_0.plot(kind='line', x='PAY_0', y='residual_1', color='deeppink', \n",
    "                       linestyle='--', ax=ax1)\n",
    "\n",
    "# partial dependence and ICE ###################################################\n",
    "\n",
    "plot_par_dep_ICE('PAY_0', par_dep_PAY_0.drop(['residual_0', 'residual_1'], \n",
    "                                             axis=1), \n",
    "                  ax2, ticks, labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These three plots together are highly informative.\n",
    "\n",
    "\n",
    "* The monotonicity of the learned GBM response function has been confirmed at many percentiles of model predictions locally and on average globally.\n",
    "\n",
    "\n",
    "* In general there is not much real data for `PAY_0 > 2`, so predictions in that range are low-confidence, no matter what the modeled probability is. Luckily this model was trained with monotonicity constraints and it carries the predictions from `PAY_0 = 2` forward even into out-of-range data. This seems reasonable. However new customers with `PAY_0 > 2` could also be handed over to human case workers or to a more transparent business rule system to be even more cautious.\n",
    "\n",
    "\n",
    "* This model treats missing data with lower probability of default than someone who paid their most recent bill in-full. This seems worrisome from a predictive accuracy, model drift, and security perspective. Logically, why would `NaN == -2`? Also, `PAY_0` is the most important variable in the model. Setting it to missing would often result in a customer being seen as likely to pay future bills. Is this prediction behavior prudent from a adversarial, drift, or security standpoint?\n",
    "\n",
    "\n",
    "* Partial dependence and ICE curves do not diverge, indicating that partial dependence is trustworthy and representative of local behavior and also that strong interactions with other variables are likely not affecting model predictions w.r.t. `PAY_0` _in the observed test set_.\n",
    "\n",
    "\n",
    "* The customer at the 90th percentile of predicted probability of default has the largest observed swing of prediction values across the domain of `PAY_0`. This information will guide a search for adversarial examples in Section 5.\n",
    "\n",
    "\n",
    "* The distribution of actual payments and defaults is fairly equal for high values of `PAY_0`, say `PAY_0` > 3, and yet when the scenario in which `PAY_0` is high for everyone is simulated, this leads to both high predicted probabilities and large residuals for `DEFAULT_NEXT_MONTH = 0` individuals. In this case, the inputs to the model changed, but not the labels, so this means that the situation in which someone has paid their bill, but has bad values for `PAY_0`, the model to generates high probabilities of default, and will lead to large errors. *A mechanism for error* has been identified: over-emphasis of a feature. I.e. `PAY_0 > 2` leads to high error when someone does pay their bill the next month.\n",
    "\n",
    "\n",
    "* This over-emphasis on `PAY_0` could be removed from the model by some means. Potentially by editing the final model artifact, or by injection of missing values or regularization during training, or by missing value injection based on assertions during scoring. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 5. Adversarial Examples\n",
    "\n",
    "The GBM model is highly sensitive to `PAY_0` values, but what other variable's values have a large impact on model predictions? In this section, brute-force searches will be conducted for rows of data, known as _adversarial examples_, that exert a strong influence on the trained model. Information learned from Shapley values and ICE will guide a search for rows that can swing model predictions high and low. These rows are particularly interesting from a drift and security viewpoint. If market conditions change so that high-impact values of important features are more common, e.g. a recession, then this search will help users understand potential future model behavior. Combinations of variables with strong effects can also be recorded and then monitored for in real-time as an active preventative measure against malicious adversarial attacks. Then a search for adversarial examples that minimize model residuals for high-residual customers will also be conducted to confirm, isolate, or remediate any previously known or unknown error mechanisms. Finally, a search for combinations of the demographic variables, `AGE`, `SEX`, `MARRIAGE`, and `EDUCATION`, that have a strong effect on model predictions will be undertaken to help elucidate any unforeseen disparate impact problems. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Conduct adversarial example search over important variables for an interesting row\n",
    "In the ICE plot in Section 4, the customer at the 90th percentile of predicted probability of default was shown to have a high degree of variability in their predictions across the values of `PAY_0`. The row will serve as a prototype in a search for adversarial examples."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The original row, used as prototype \n",
    "For reference, the values for each variable in the prototype row are displayed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        vertical-align: middle;\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <th>SEX</th>\n",
       "      <th>EDUCATION</th>\n",
       "      <th>MARRIAGE</th>\n",
       "      <th>AGE</th>\n",
       "      <th>PAY_0</th>\n",
       "      <th>PAY_2</th>\n",
       "      <th>PAY_3</th>\n",
       "      <th>PAY_4</th>\n",
       "      <th>PAY_5</th>\n",
       "      <th>PAY_6</th>\n",
       "      <th>BILL_AMT1</th>\n",
       "      <th>BILL_AMT2</th>\n",
       "      <th>BILL_AMT3</th>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <th>PAY_AMT6</th>\n",
       "      <th>DEFAULT_NEXT_MONTH</th>\n",
       "      <th>p_DEFAULT_NEXT_MONTH</th>\n",
       "      <th>r_DEFAULT_NEXT_MONTH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <td>40000</td>\n",
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       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>22969</td>\n",
       "      <td>1326</td>\n",
       "      <td>1355</td>\n",
       "      <td>1668</td>\n",
       "      <td>807</td>\n",
       "      <td>834</td>\n",
       "      <td>837</td>\n",
       "      <td>1</td>\n",
       "      <td>0.595022</td>\n",
       "      <td>0.519157</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         ID  LIMIT_BAL  SEX  EDUCATION  MARRIAGE  AGE  PAY_0  PAY_2  PAY_3  \\\n",
       "5594  18421      40000    2          2         2   24      2      0      0   \n",
       "\n",
       "      PAY_4  PAY_5  PAY_6  BILL_AMT1  BILL_AMT2  BILL_AMT3  BILL_AMT4  \\\n",
       "5594      0      0      0      19012      20018      21047      22360   \n",
       "\n",
       "      BILL_AMT5  BILL_AMT6  PAY_AMT1  PAY_AMT2  PAY_AMT3  PAY_AMT4  PAY_AMT5  \\\n",
       "5594      22499      22969      1326      1355      1668       807       834   \n",
       "\n",
       "      PAY_AMT6  DEFAULT_NEXT_MONTH  p_DEFAULT_NEXT_MONTH  r_DEFAULT_NEXT_MONTH  \n",
       "5594       837                   1              0.595022              0.519157  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yhat_test[yhat_test['ID'] == yhat_percentile_dict[90]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Function to find adversarial examples\n",
    "The search for adversarial examples takes a prototype row, perturbs the values of certain variables in the row, and records the new prediction and residual for each new perturbed row. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def find_adversaries(xs, frame, model, row_id, oor_proportion=0.1, \n",
    "                     resolution=10, verbose=False):  \n",
    "    \n",
    "    \"\"\" A brute force function to find adversaries. Dynamically generates nested loops\n",
    "        to populate adversary_frame with perturbed values and their predictions\n",
    "        and logloss residuals.\n",
    "        \n",
    "        ASSUMES global vars y, yhat, and resid have been defined previously.\n",
    "        \n",
    "    Args:    \n",
    "        xs: List of variables over which to find adversaries.\n",
    "        frame: Pandas DataFrame for which to calculate bounds for adversary search.\n",
    "               row_id is assumed to be in frame.\n",
    "        model: Model to use in adversary search.\n",
    "        row_id: Prototype row on which the search is based.\n",
    "        oor_proportion: The proportion by which the search can exceed minimum and \n",
    "                        maximum values in frame. Must be between 0-1, default 0.1.\n",
    "        resolution: The number of points across the domain of xs for which \n",
    "                    to search for adversaries, default 10 due to deep nesting.\n",
    "        verbose: Boolean, whether to print generated code statements.\n",
    "                \n",
    "    Returns: \n",
    "        Frame containing all tested values and their associated predictions \n",
    "        and logloss residuals. \n",
    "    \n",
    "    \"\"\"\n",
    "    \n",
    "    # init dicts to hold bin values\n",
    "    bins_dict = {}\n",
    "    \n",
    "    # find boundaries, bins and record \n",
    "    for j in xs:\n",
    "        \n",
    "        min_ = frame[j].min()\n",
    "        max_ = frame[j].max()\n",
    "        min_ = min_ - np.abs(oor_proportion*min_)\n",
    "        max_ = max_ + np.abs(oor_proportion*max_)\n",
    "        by = (max_ - min_)/resolution\n",
    "        # modify max and by \n",
    "        # to preserve resolution and actually search up to max\n",
    "        bins_dict[j] = np.arange(min_, (max_ + by), (by + np.round((1. / resolution) * by, 3)))\n",
    "        bins_dict[j] = np.round_(bins_dict[j], 6)  # reasonable precision\n",
    "    \n",
    "    # initialize prototype row\n",
    "    # deep copy to prevent corruption of original data\n",
    "    row = frame[frame['ID'] == row_id].copy(deep=True)\n",
    "    \n",
    "    # generate nested loops dynamically ############################################\n",
    "    # to search all vals in all search cols\n",
    "    \n",
    "    # init true tab\n",
    "    # define code variable and init returned Pandas DataFrame, adversary_frame\n",
    "    tab = '    '\n",
    "    code = 'global adversary_frame\\n'\n",
    "    code += 'adversary_frame = pd.DataFrame(columns=xs + [yhat, resid])\\n'\n",
    "\n",
    "    # generate for loop statements for search\n",
    "    for i, j in enumerate(xs):\n",
    "        code += i*tab + 'for ' + string.ascii_lowercase[i] + ' in ' +\\\n",
    "            str(list(bins_dict[j])) + ':\\n'\n",
    "            \n",
    "    # generate value assignment statements to perturb search vars\n",
    "    for k, j in enumerate(xs):\n",
    "        code += (i + 1)*tab + 'row[\"' + j + '\"] = ' + string.ascii_lowercase[k] +\\\n",
    "            '\\n'\n",
    "    \n",
    "    # generate progress reporting statements  \n",
    "    # generate statements for appending test values, preds, and resids to adversary_frame\n",
    "    # uses only absolute residuals to avoid averaging problems between 0/1 target classes\n",
    "    code += (i + 1)*tab + 'if (adversary_frame.shape[0] + 1) % 1000 == 0:\\n'\n",
    "    code += (i + 2)*tab +\\\n",
    "        'print(\"Built %i/%i rows ...\" % (adversary_frame.shape[0] + 1, (resolution)**(i+1)))\\n'\n",
    "    code += (i + 1)*tab +\\\n",
    "        'adversary_frame = adversary_frame.append(row, ignore_index=True, sort=False)\\n' \n",
    "    code += 'print(\"Scoring ...\")\\n'\n",
    "    code += 'adversary_frame[yhat] = model.predict(xgb.DMatrix(adversary_frame[model.feature_names]), ntree_limit=model.best_ntree_limit)\\n'\n",
    "    code += 'adversary_frame[resid] = np.abs(adversary_frame[y]*np.log(adversary_frame[yhat]) - (1 - adversary_frame[y])*np.log(1 - adversary_frame[yhat]))\\n'\n",
    "    code += 'print(\"Done.\")'\n",
    "    \n",
    "    if verbose:\n",
    "        print('Executing:')\n",
    "        print(code)\n",
    "        print('--------------------------------------------------------------------------------')\n",
    "    \n",
    "    # execute generated code\n",
    "    exec(code)\n",
    "    \n",
    "    return adversary_frame\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Due to fluctuations observed in the ICE plot above, the customer at the 90th percentile of probability of default will serve as the prototype row. In the Shapley summary plot in Section 3, `PAY_0`, `PAY_3`, `PAY_AMT1`, and `PAY_AMT2`, exhibit the most extreme local prediction contributions. The search for adversarial examples will be conducted over perturbations of these four variables. The search will consider 10,000 permutations of `PAY_0`, `PAY_3`, `PAY_AMT1`, and `PAY_AMT2` to find adversarial examples with the largest impact on model predictions and to understand the contributions and interactions of these variables in the model in general."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Built 1000/10000 rows ...\n",
      "Built 2000/10000 rows ...\n",
      "Built 3000/10000 rows ...\n",
      "Built 4000/10000 rows ...\n",
      "Built 5000/10000 rows ...\n",
      "Built 6000/10000 rows ...\n",
      "Built 7000/10000 rows ...\n",
      "Built 8000/10000 rows ...\n",
      "Built 9000/10000 rows ...\n",
      "Built 10000/10000 rows ...\n",
      "Scoring ...\n",
      "Done.\n"
     ]
    }
   ],
   "source": [
    "res_ = 10 # keep resolution small to avoid long run time\n",
    "\n",
    "# four variables with widest Shapley contribs\n",
    "search_cols = ['PAY_0', 'PAY_3', 'PAY_AMT1', 'PAY_AMT2'] \n",
    "\n",
    "# execute search\n",
    "yhat_adversaries = find_adversaries(search_cols, test, xgb_model, yhat_percentile_dict[90], resolution=res_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Adversarial examples that minimize model predictions\n",
    "These, and similar, rows minimize the predicted probability of default for the prototype row. They could be used by a malicious attacker in an integrity attack using hacked or falsified application information to maximize their chance at receiving undeserved credit line increases, loans, or other financially beneficial outcomes. These rows should be recorded and monitored for after the model is deployed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PAY_0</th>\n",
       "      <th>PAY_3</th>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <th>p_DEFAULT_NEXT_MONTH</th>\n",
       "      <th>r_DEFAULT_NEXT_MONTH</th>\n",
       "      <th>ID</th>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <th>SEX</th>\n",
       "      <th>EDUCATION</th>\n",
       "      <th>MARRIAGE</th>\n",
       "      <th>AGE</th>\n",
       "      <th>PAY_2</th>\n",
       "      <th>PAY_4</th>\n",
       "      <th>PAY_5</th>\n",
       "      <th>PAY_6</th>\n",
       "      <th>BILL_AMT1</th>\n",
       "      <th>BILL_AMT2</th>\n",
       "      <th>BILL_AMT3</th>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <th>PAY_AMT6</th>\n",
       "      <th>DEFAULT_NEXT_MONTH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>-2.2</td>\n",
       "      <td>-2.2</td>\n",
       "      <td>634198.752</td>\n",
       "      <td>735359.955</td>\n",
       "      <td>0.026825</td>\n",
       "      <td>3.618438</td>\n",
       "      <td>18421.0</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>24.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>22360.0</td>\n",
       "      <td>22499.0</td>\n",
       "      <td>22969.0</td>\n",
       "      <td>1668.0</td>\n",
       "      <td>807.0</td>\n",
       "      <td>834.0</td>\n",
       "      <td>837.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>-2.2</td>\n",
       "      <td>-2.2</td>\n",
       "      <td>528498.960</td>\n",
       "      <td>294143.982</td>\n",
       "      <td>0.026825</td>\n",
       "      <td>3.618438</td>\n",
       "      <td>18421.0</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19012.0</td>\n",
       "      <td>20018.0</td>\n",
       "      <td>21047.0</td>\n",
       "      <td>22360.0</td>\n",
       "      <td>22499.0</td>\n",
       "      <td>22969.0</td>\n",
       "      <td>1668.0</td>\n",
       "      <td>807.0</td>\n",
       "      <td>834.0</td>\n",
       "      <td>837.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>-2.2</td>\n",
       "      <td>-2.2</td>\n",
       "      <td>528498.960</td>\n",
       "      <td>147071.991</td>\n",
       "      <td>0.026825</td>\n",
       "      <td>3.618438</td>\n",
       "      <td>18421.0</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19012.0</td>\n",
       "      <td>20018.0</td>\n",
       "      <td>21047.0</td>\n",
       "      <td>22360.0</td>\n",
       "      <td>22499.0</td>\n",
       "      <td>22969.0</td>\n",
       "      <td>1668.0</td>\n",
       "      <td>807.0</td>\n",
       "      <td>834.0</td>\n",
       "      <td>837.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    PAY_0  PAY_3    PAY_AMT1    PAY_AMT2  p_DEFAULT_NEXT_MONTH  \\\n",
       "65   -2.2   -2.2  634198.752  735359.955              0.026825   \n",
       "52   -2.2   -2.2  528498.960  294143.982              0.026825   \n",
       "51   -2.2   -2.2  528498.960  147071.991              0.026825   \n",
       "\n",
       "    r_DEFAULT_NEXT_MONTH       ID  LIMIT_BAL  SEX  EDUCATION  MARRIAGE   AGE  \\\n",
       "65              3.618438  18421.0    40000.0  2.0        2.0       2.0  24.0   \n",
       "52              3.618438  18421.0    40000.0  2.0        2.0       2.0  24.0   \n",
       "51              3.618438  18421.0    40000.0  2.0        2.0       2.0  24.0   \n",
       "\n",
       "    PAY_2  PAY_4  PAY_5  PAY_6  BILL_AMT1  BILL_AMT2  BILL_AMT3  BILL_AMT4  \\\n",
       "65    0.0    0.0    0.0    0.0    19012.0    20018.0    21047.0    22360.0   \n",
       "52    0.0    0.0    0.0    0.0    19012.0    20018.0    21047.0    22360.0   \n",
       "51    0.0    0.0    0.0    0.0    19012.0    20018.0    21047.0    22360.0   \n",
       "\n",
       "    BILL_AMT5  BILL_AMT6  PAY_AMT3  PAY_AMT4  PAY_AMT5  PAY_AMT6  \\\n",
       "65    22499.0    22969.0    1668.0     807.0     834.0     837.0   \n",
       "52    22499.0    22969.0    1668.0     807.0     834.0     837.0   \n",
       "51    22499.0    22969.0    1668.0     807.0     834.0     837.0   \n",
       "\n",
       "    DEFAULT_NEXT_MONTH  \n",
       "65                 1.0  \n",
       "52                 1.0  \n",
       "51                 1.0  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yhat_adversaries.sort_values(by=yhat).head(n=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Adversarial examples that maximize model predictions\n",
    "These, and similar, rows maximize the predicted probability of default for the prototype row. They could be used by a malicious attacker in a hacked or falsified application in a denial-of-service (DOS) attack to minimize another customer's chances of receiving credit line increases, loans, or other financially beneficial outcomes. These rows should be recorded and monitored for after the model is deployed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0.60917</td>\n",
       "      <td>0.495658</td>\n",
       "      <td>18421.0</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19012.0</td>\n",
       "      <td>20018.0</td>\n",
       "      <td>21047.0</td>\n",
       "      <td>22360.0</td>\n",
       "      <td>22499.0</td>\n",
       "      <td>22969.0</td>\n",
       "      <td>1668.0</td>\n",
       "      <td>807.0</td>\n",
       "      <td>834.0</td>\n",
       "      <td>837.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      PAY_0  PAY_3  PAY_AMT1  PAY_AMT2  p_DEFAULT_NEXT_MONTH  \\\n",
       "7900   6.27   8.69       0.0       0.0               0.60917   \n",
       "7600   6.27   5.06       0.0       0.0               0.60917   \n",
       "6600   5.06   5.06       0.0       0.0               0.60917   \n",
       "\n",
       "      r_DEFAULT_NEXT_MONTH       ID  LIMIT_BAL  SEX  EDUCATION  MARRIAGE  \\\n",
       "7900              0.495658  18421.0    40000.0  2.0        2.0       2.0   \n",
       "7600              0.495658  18421.0    40000.0  2.0        2.0       2.0   \n",
       "6600              0.495658  18421.0    40000.0  2.0        2.0       2.0   \n",
       "\n",
       "       AGE  PAY_2  PAY_4  PAY_5  PAY_6  BILL_AMT1  BILL_AMT2  BILL_AMT3  \\\n",
       "7900  24.0    0.0    0.0    0.0    0.0    19012.0    20018.0    21047.0   \n",
       "7600  24.0    0.0    0.0    0.0    0.0    19012.0    20018.0    21047.0   \n",
       "6600  24.0    0.0    0.0    0.0    0.0    19012.0    20018.0    21047.0   \n",
       "\n",
       "      BILL_AMT4  BILL_AMT5  BILL_AMT6  PAY_AMT3  PAY_AMT4  PAY_AMT5  PAY_AMT6  \\\n",
       "7900    22360.0    22499.0    22969.0    1668.0     807.0     834.0     837.0   \n",
       "7600    22360.0    22499.0    22969.0    1668.0     807.0     834.0     837.0   \n",
       "6600    22360.0    22499.0    22969.0    1668.0     807.0     834.0     837.0   \n",
       "\n",
       "      DEFAULT_NEXT_MONTH  \n",
       "7900                 1.0  \n",
       "7600                 1.0  \n",
       "6600                 1.0  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yhat_adversaries.sort_values(by=yhat).tail(n=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Function for visual summary of adversary search results.\n",
    "This function groups the DataFrame by two search variables and uses a custom descriptive statistic to summarize the group in terms of predictions or residuals. The summarized value is then plotted on a surface in terms of the two groupby variables. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_sm_3d(frame, resolution, search_cols, z_axis_var, stat):\n",
    "\n",
    "    \"\"\"Plots 6 small multiples in a grouped subplot to display adversary search \n",
    "       results from find_adversaries.\n",
    "    \n",
    "    Args:\n",
    "        frame: Pandas DataFrame containing potential adversaries generated by \n",
    "               find_adversaries.\n",
    "        resolution: The number of points across the domain of the variables in \n",
    "                    search_cols in find_adversaries. \n",
    "        search_cols: List of search_cols used in find_adversaries.\n",
    "        z_axis_var: The name of the variable by which to group the frame and\n",
    "                    that will appear in the title and z-axis label of the \n",
    "                    generated plot.\n",
    "        stat: Groupby stat for z_axis_var and frame.\n",
    "    \n",
    "    \"\"\"\n",
    "    \n",
    "    max_ = frame[z_axis_var].max() # establish z-axis high limit\n",
    "    \n",
    "    fig = plt.figure(figsize=plt.figaspect(0.67)*2.5) # init 2 x 3 plot\n",
    "\n",
    "    _2d_shape = (resolution, resolution) # correct shape for 3-D display of 1-D arrays\n",
    "\n",
    "    # loop through 2-way combos of search_cols\n",
    "    for i, two_way_combo in enumerate(list(combinations(search_cols, 2))):\n",
    "\n",
    "        # many unique values exist for each 2-way combo of search_cols values \n",
    "        # summarize by stat to plot concisely\n",
    "        \n",
    "        # execute groupby\n",
    "        groups = eval('frame[[two_way_combo[0], two_way_combo[1], z_axis_var]]\\\n",
    "                        .groupby([two_way_combo[0], two_way_combo[1]]).' + stat + '()')\n",
    "\n",
    "        groups = groups.reset_index() # convert groupby vals to cols (from index)\n",
    "\n",
    "        ax = fig.add_subplot(2, 3, (i + 1), projection='3d') # subplot placement\n",
    "            \n",
    "        # values and labels for each axis\n",
    "        x = np.asarray(groups[two_way_combo[0]]).reshape(_2d_shape)\n",
    "        ax.set_xlabel('\\n' + two_way_combo[0])\n",
    "        y = np.asarray(groups[two_way_combo[1]]).reshape(_2d_shape)\n",
    "        ax.set_ylabel('\\n' + two_way_combo[1])\n",
    "        z = np.asarray(groups[z_axis_var]).reshape(_2d_shape)\n",
    "        ax.set_zlabel('\\n' + stat + ' ' + str(z_axis_var))\n",
    "        ax.set_zlim3d(0, max_) # ensure constant scale\n",
    "        \n",
    "        # plot\n",
    "        surf = ax.plot_surface(x, y, z, \n",
    "                               cmap=cm.coolwarm, \n",
    "                               linewidth=0.05, \n",
    "                               rstride=1, \n",
    "                               cstride=1, \n",
    "                               antialiased=True)\n",
    "        \n",
    "    \n",
    "    # main title and display    \n",
    "    fig.suptitle(stat.title() + ' ' + str(z_axis_var) + ' for ' + str(search_cols))    \n",
    "    plt.tight_layout()\n",
    "    _ = plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Maximum predictions across pairs of search variables\n",
    "The plots below show the maximum model prediction generated by an adversary in terms of values of the search variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff70f68d320>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_sm_3d(yhat_adversaries, res_, search_cols, yhat, 'max') # plot max prediction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The search has revealed several interesting patterns: \n",
    "\n",
    "* The monotonicity of the learned GBM response function was preserved across this set of variables.\n",
    "\n",
    "\n",
    "* Another potential error mechanism has been discovered: non-robust interaction features. Due to the PDP and ICE for `PAY_0` showing no evidence of strong interactions with other variables, there appear to be some interactions between `PAY_0`, `PAY_AMT1`, and `PAY_AMT2`, which may not be observed in the training or validation data, but that have a strong effect on model predictions. They should be remediated from the model by some method. For instance high `PAY_0` values and high `PAY_AMT1` values seem to have a strong effect on model predictions, but are likely unrealistic and unobserved, because at a certain point, `PAY_AMT1` values exceed a customer's `LIMIT_BAL` -- meaning they cannot technically default. If the impact of this interaction is somehow remediated, potentially by editing the final model artifact or by injection of missing values or regularization during training or missing value injection based on assertions during scoring, that could possibly lead to more accurate model predictions on future data.\n",
    "\n",
    "\n",
    "* This model is vulnerable to adversarial attack, especially using `PAY_0` and `PAY_3`. Obvious combinations of values for `PAY_0` and `PAY_3` lead to extreme predicted probabilities of default, but so do other combinations of the repayment status and payment amount variables. Perhaps more surprisingly, combinations of low values for the payment amount variables alone can also lead to high predictions. These payment amount value combinations could be the more subtle route for an adversarial denial-of-service (DOS) attack. Active counter-measures should be considered.\n",
    "\n",
    "\n",
    "* Users should investigate these patterns to get a sense for how their model might perform if data drifts in any of the searched directions."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  Conduct adversarial example search over high-residual rows"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By attempting to decrease the residual of a high-error row, it may be possible to decrease the overall error of the model or to learn more about general error mechanisms in the model."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### High-residual prototype row\n",
    "A customer with a high residual will serve as the prototype row for a search to reduce residual values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <th>SEX</th>\n",
       "      <th>EDUCATION</th>\n",
       "      <th>MARRIAGE</th>\n",
       "      <th>AGE</th>\n",
       "      <th>PAY_0</th>\n",
       "      <th>PAY_2</th>\n",
       "      <th>PAY_3</th>\n",
       "      <th>PAY_4</th>\n",
       "      <th>PAY_5</th>\n",
       "      <th>PAY_6</th>\n",
       "      <th>BILL_AMT1</th>\n",
       "      <th>BILL_AMT2</th>\n",
       "      <th>BILL_AMT3</th>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <th>PAY_AMT6</th>\n",
       "      <th>DEFAULT_NEXT_MONTH</th>\n",
       "      <th>p_DEFAULT_NEXT_MONTH</th>\n",
       "      <th>r_DEFAULT_NEXT_MONTH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2083</th>\n",
       "      <td>6898</td>\n",
       "      <td>120000</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>60316</td>\n",
       "      <td>61763</td>\n",
       "      <td>63154</td>\n",
       "      <td>64524</td>\n",
       "      <td>66345</td>\n",
       "      <td>68104</td>\n",
       "      <td>3000</td>\n",
       "      <td>3000</td>\n",
       "      <td>3000</td>\n",
       "      <td>3000</td>\n",
       "      <td>3000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.584431</td>\n",
       "      <td>0.537117</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        ID  LIMIT_BAL  SEX  EDUCATION  MARRIAGE  AGE  PAY_0  PAY_2  PAY_3  \\\n",
       "2083  6898     120000    1          2         2   32      1      2      2   \n",
       "\n",
       "      PAY_4  PAY_5  PAY_6  BILL_AMT1  BILL_AMT2  BILL_AMT3  BILL_AMT4  \\\n",
       "2083      2      2      2      60316      61763      63154      64524   \n",
       "\n",
       "      BILL_AMT5  BILL_AMT6  PAY_AMT1  PAY_AMT2  PAY_AMT3  PAY_AMT4  PAY_AMT5  \\\n",
       "2083      66345      68104      3000      3000      3000      3000      3000   \n",
       "\n",
       "      PAY_AMT6  DEFAULT_NEXT_MONTH  p_DEFAULT_NEXT_MONTH  r_DEFAULT_NEXT_MONTH  \n",
       "2083         0                   1              0.584431              0.537117  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resid_percentile_dict = get_percentile_dict(resid, 'ID', yhat_test) # dictionary of row ID and residuals\n",
    "high_row = yhat_test[yhat_test['ID'] == resid_percentile_dict[80]] # take customer with high residual\n",
    "high_row # display"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Execute search and visually summarize adversaries\n",
    "This search will be over the same combinations of `PAY_0`, `PAY_3`, `PAY_AMT1`, and `PAY_AMT2`, but results will be analyzed in terms of minimum residual instead of maximum prediction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Built 1000/10000 rows ...\n",
      "Built 2000/10000 rows ...\n",
      "Built 3000/10000 rows ...\n",
      "Built 4000/10000 rows ...\n",
      "Built 5000/10000 rows ...\n",
      "Built 6000/10000 rows ...\n",
      "Built 7000/10000 rows ...\n",
      "Built 8000/10000 rows ...\n",
      "Built 9000/10000 rows ...\n",
      "Built 10000/10000 rows ...\n",
      "Scoring ...\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff71258d898>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# four variables with widest Shapley contribs\n",
    "search_cols = ['PAY_0', 'PAY_3', 'PAY_AMT1', 'PAY_AMT2'] \n",
    "\n",
    "# search for high-residual adversaries\n",
    "high_resid_adversaries = find_adversaries(search_cols, test, xgb_model, resid_percentile_dict[80], resolution=res_)\n",
    "\n",
    "# plot minimum residual\n",
    "plot_sm_3d(high_resid_adversaries, res_, search_cols, resid, 'min')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These results basically confirm the findings from the search over predictions for these same variables above and from ICE plots. Interactions with low `PAY_3` values or high `PAY_AMT1` and high `PAY_AMT2` values do worsen the over emphasis on `PAY_0` in ways that seem robust, just too dramatic. Interestingly, low `PAY_0` and high `PAY_AMT2` values exhibit the highest residual for this relatively high-risk individual. Also, the same non-robust lack of sensitivity to `PAY_AMT`* variables is observed when `PAY_0` is high. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  Conduct adversarial example search over `AGE`, `EDUCATION`, `SEX` and `MARRIAGE` \n",
    "This search will look for combinations of demographic segments that may experience disparate impact under the trained model. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Partial dependence and ICE for AGE\n",
    "ICE will be used again to select a prototype row with predictions that vary with `AGE`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff712240ef0>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_par_dep_ICE('AGE', par_dep_AGE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Prototype row for demographic search\n",
    "The prototype row for the demographic adversary search is a relatively young married male with a graduate education."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <th>SEX</th>\n",
       "      <th>EDUCATION</th>\n",
       "      <th>MARRIAGE</th>\n",
       "      <th>AGE</th>\n",
       "      <th>PAY_0</th>\n",
       "      <th>PAY_2</th>\n",
       "      <th>PAY_3</th>\n",
       "      <th>PAY_4</th>\n",
       "      <th>PAY_5</th>\n",
       "      <th>PAY_6</th>\n",
       "      <th>BILL_AMT1</th>\n",
       "      <th>BILL_AMT2</th>\n",
       "      <th>BILL_AMT3</th>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <th>PAY_AMT6</th>\n",
       "      <th>DEFAULT_NEXT_MONTH</th>\n",
       "      <th>p_DEFAULT_NEXT_MONTH</th>\n",
       "      <th>r_DEFAULT_NEXT_MONTH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2272</th>\n",
       "      <td>7411</td>\n",
       "      <td>20000</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>52</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15768</td>\n",
       "      <td>16792</td>\n",
       "      <td>18105</td>\n",
       "      <td>18157</td>\n",
       "      <td>18538</td>\n",
       "      <td>19200</td>\n",
       "      <td>1285</td>\n",
       "      <td>1598</td>\n",
       "      <td>650</td>\n",
       "      <td>674</td>\n",
       "      <td>971</td>\n",
       "      <td>580</td>\n",
       "      <td>0</td>\n",
       "      <td>0.236098</td>\n",
       "      <td>0.269315</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        ID  LIMIT_BAL  SEX  EDUCATION  MARRIAGE  AGE  PAY_0  PAY_2  PAY_3  \\\n",
       "2272  7411      20000    1          2         1   52      0      0      0   \n",
       "\n",
       "      PAY_4  PAY_5  PAY_6  BILL_AMT1  BILL_AMT2  BILL_AMT3  BILL_AMT4  \\\n",
       "2272      0      0      0      15768      16792      18105      18157   \n",
       "\n",
       "      BILL_AMT5  BILL_AMT6  PAY_AMT1  PAY_AMT2  PAY_AMT3  PAY_AMT4  PAY_AMT5  \\\n",
       "2272      18538      19200      1285      1598       650       674       971   \n",
       "\n",
       "      PAY_AMT6  DEFAULT_NEXT_MONTH  p_DEFAULT_NEXT_MONTH  r_DEFAULT_NEXT_MONTH  \n",
       "2272       580                   0              0.236098              0.269315  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yhat_test[yhat_test['ID'] == yhat_percentile_dict[70]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Execute and visually summarize adversaries\n",
    "Search for adversaries whose predictions change widely due to changes in demographic variables. This search will be analyzed in terms of maximum prediction for each tested combination of  `AGE`, `EDUCATION`, `SEX` and `MARRIAGE`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Built 1000/10000 rows ...\n",
      "Built 2000/10000 rows ...\n",
      "Built 3000/10000 rows ...\n",
      "Built 4000/10000 rows ...\n",
      "Built 5000/10000 rows ...\n",
      "Built 6000/10000 rows ...\n",
      "Built 7000/10000 rows ...\n",
      "Built 8000/10000 rows ...\n",
      "Built 9000/10000 rows ...\n",
      "Built 10000/10000 rows ...\n",
      "Scoring ...\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff711cc3320>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "search_cols = ['AGE', 'EDUCATION', 'SEX', 'MARRIAGE'] \n",
    "\n",
    "# execute search\n",
    "dem_adversaries = find_adversaries(search_cols, test, xgb_model, yhat_percentile_dict[80], resolution=res_)\n",
    "plot_sm_3d(dem_adversaries, res_, search_cols, yhat, 'max') # display max change in predictions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From this search, it can be seen that:\n",
    "\n",
    "\n",
    "* `EDUCATION` has little impact on model predictions.\n",
    "\n",
    "\n",
    "* Even high-degree interactions of demographic variables do not swing model predictions drastically compared to other important variables, however several subgroups do appear to have higher predictions for probability of default:\n",
    "\n",
    "  * Older male customers\n",
    "  * Older married customers\n",
    "  * Married male customers\n",
    "  \n",
    "\n",
    "* A more detailed analysis of disparate impact should always be conducted for models that affect people, however this adversary search has indicated that certain subgroups maybe be at higher risk of disparate impact for this model. For an example of a basic disparate impact analysis, please see: https://github.com/jphall663/interpretable_machine_learning_with_python/blob/master/dia.ipynb.\n",
    "\n",
    "\n",
    "* If the interactions described above appear non-robust they could be removed from the model by some means, potentially by editing the final model artifact or by injection of missing values or regularization during training or missing value injection based on assertions during scoring.  \n",
    "\n",
    "\n",
    "* Impersonation attacks seem potentially less damaging than standard adversarial example attacks. \n",
    "\n",
    "\n",
    "* These patterns should also be considered in the context of model drift, if the customer population gets older, more male, or contains more married customers, this model indicates much higher levels of risk may be present."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 6. Bonus: Random Attacks\n",
    "Random attacks expose a model to random data in an attempt to discover patterns or problems structured or guided searches may not reveal. As the nonlinear or interaction complexity of machine learning models may simply be incomprehensible to human users in some cases, exposure to random data may help reveal unforeseen, unaccounted for, or previously unknown problems. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Function for random attacks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "def random_attack(X, frame, model, oor_proportion=0.33, N=10000, \n",
    "                  inject_missing=True, missing_proportion=0.15, seed=12345):\n",
    "\n",
    "    \"\"\" Generates random data and scores model on random data.\n",
    "\n",
    "    Args:\n",
    "        X: Input variables for model in frame.\n",
    "        frame: Pandas DataFrame for which to calculate bounds \n",
    "               for random data, should contain X.\n",
    "        model: Model to score on random data.\n",
    "        oor_proportion: The proportion by which the random values can \n",
    "                        exceed minimum and maximum values in frame. \n",
    "                        Must be between 0-1, default 0.33.\n",
    "        N: Number of random samples to generate.\n",
    "        inject_missing: Whether to randomly inject missing values into \n",
    "                        generated frame.\n",
    "        missing_proportion: The proportion of random values to be  \n",
    "                            replaced by nan. Must be between 0-1, \n",
    "                            default 0.15.\n",
    "        seed: Seed to enforce reproducibility. \n",
    "\n",
    "    Returns:\n",
    "        Scored random frame.\n",
    "\n",
    "    \"\"\"\n",
    "    \n",
    "    # init random frame\n",
    "    random_frame = pd.DataFrame(columns=X, index=np.arange(N))\n",
    "    \n",
    "    # find bounds for each j and generate random data\n",
    "    for j in X:\n",
    "        \n",
    "        min_ = frame[j].min()\n",
    "        max_ = frame[j].max()\n",
    "        \n",
    "        np.random.seed(seed) # ensure column bounds are set similary \n",
    "        random_frame[j] =\\\n",
    "            np.random.uniform(low=(min_ - np.abs(oor_proportion*min_)),\n",
    "                              high=(max_ + np.abs(oor_proportion*max_)),\n",
    "                              size=(N,)) \n",
    "        \n",
    "        # ensure treatment as numeric\n",
    "        random_frame[j] = pd.to_numeric(random_frame[j])\n",
    "        \n",
    "    if inject_missing:\n",
    "        \n",
    "        np.random.seed(seed) # ensure nan is injected similarly       \n",
    "        random_frame =\\\n",
    "            random_frame.mask(np.random.random(random_frame.shape) < missing_proportion)    \n",
    "    \n",
    "    # score\n",
    "    random_frame[yhat] = model.predict(xgb.DMatrix(random_frame[model.feature_names]), \n",
    "                                       ntree_limit=model.best_ntree_limit)\n",
    "\n",
    "    return random_frame\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Execute random attacks with and without missing values\n",
    "Partial dependence and ICE revealed a potentially worrisome correlation between low predicted probabilities and missing values. Missingness' effect on the model predictions will also be considered here, as well as problems not considered earlier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run largish random attack\n",
    "N_ = 1000000\n",
    "randoms_w_miss = random_attack(X, test, xgb_model, N=N_)\n",
    "randoms_wo_miss = random_attack(X, test, xgb_model, N=N_, inject_missing=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Confirm the only difference between the two random attacks is the presence of missing values\n",
    "In the two sets below, the only apparent difference between them appears to be the presence of missing values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <th>SEX</th>\n",
       "      <th>EDUCATION</th>\n",
       "      <th>MARRIAGE</th>\n",
       "      <th>AGE</th>\n",
       "      <th>PAY_0</th>\n",
       "      <th>PAY_2</th>\n",
       "      <th>PAY_3</th>\n",
       "      <th>PAY_4</th>\n",
       "      <th>PAY_5</th>\n",
       "      <th>PAY_6</th>\n",
       "      <th>BILL_AMT1</th>\n",
       "      <th>BILL_AMT2</th>\n",
       "      <th>BILL_AMT3</th>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <th>PAY_AMT6</th>\n",
       "      <th>p_DEFAULT_NEXT_MONTH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.236861e+06</td>\n",
       "      <td>2.519936</td>\n",
       "      <td>7.418336</td>\n",
       "      <td>3.709168</td>\n",
       "      <td>93.719507</td>\n",
       "      <td>9.703894</td>\n",
       "      <td>9.703894</td>\n",
       "      <td>9.703894</td>\n",
       "      <td>9.703894</td>\n",
       "      <td>9.703894</td>\n",
       "      <td>9.703894</td>\n",
       "      <td>1.178004e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.101620e+06</td>\n",
       "      <td>1.140599e+06</td>\n",
       "      <td>1.174860e+06</td>\n",
       "      <td>1.080050e+06</td>\n",
       "      <td>1.502795e+06</td>\n",
       "      <td>1.107854e+06</td>\n",
       "      <td>767797.819540</td>\n",
       "      <td>383447.627638</td>\n",
       "      <td>651754.019301</td>\n",
       "      <td>0.703498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.253598e+05</td>\n",
       "      <td>1.299587</td>\n",
       "      <td>2.524677</td>\n",
       "      <td>1.262338</td>\n",
       "      <td>41.177058</td>\n",
       "      <td>1.547795</td>\n",
       "      <td>1.547795</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.547795</td>\n",
       "      <td>1.547795</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.649418e+05</td>\n",
       "      <td>352621.957687</td>\n",
       "      <td>234265.111327</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.343339e+05</td>\n",
       "      <td>2.673989e+05</td>\n",
       "      <td>3.675728e+05</td>\n",
       "      <td>5.114453e+05</td>\n",
       "      <td>3.770353e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>130498.446385</td>\n",
       "      <td>221810.961429</td>\n",
       "      <td>0.496677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.500798e+05</td>\n",
       "      <td>1.035998</td>\n",
       "      <td>1.467672</td>\n",
       "      <td>0.733836</td>\n",
       "      <td>29.828164</td>\n",
       "      <td>-0.213880</td>\n",
       "      <td>-0.213880</td>\n",
       "      <td>-0.213880</td>\n",
       "      <td>-0.213880</td>\n",
       "      <td>-0.213880</td>\n",
       "      <td>-0.213880</td>\n",
       "      <td>6.772515e+04</td>\n",
       "      <td>167389.440220</td>\n",
       "      <td>101937.093858</td>\n",
       "      <td>2.096570e+05</td>\n",
       "      <td>1.601847e+05</td>\n",
       "      <td>7.139200e+04</td>\n",
       "      <td>2.136813e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.191822e+05</td>\n",
       "      <td>151904.064128</td>\n",
       "      <td>75862.748677</td>\n",
       "      <td>128945.513811</td>\n",
       "      <td>0.032246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.773946e+05</td>\n",
       "      <td>1.077075</td>\n",
       "      <td>1.632391</td>\n",
       "      <td>0.816196</td>\n",
       "      <td>31.596725</td>\n",
       "      <td>0.060652</td>\n",
       "      <td>0.060652</td>\n",
       "      <td>0.060652</td>\n",
       "      <td>0.060652</td>\n",
       "      <td>0.060652</td>\n",
       "      <td>0.060652</td>\n",
       "      <td>9.845852e+04</td>\n",
       "      <td>196255.247953</td>\n",
       "      <td>122558.500738</td>\n",
       "      <td>2.343472e+05</td>\n",
       "      <td>1.873234e+05</td>\n",
       "      <td>1.019368e+05</td>\n",
       "      <td>2.376631e+05</td>\n",
       "      <td>3.306873e+05</td>\n",
       "      <td>2.437813e+05</td>\n",
       "      <td>168952.470865</td>\n",
       "      <td>84376.931645</td>\n",
       "      <td>143417.250160</td>\n",
       "      <td>0.013024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.579705e+05</td>\n",
       "      <td>1.799773</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.265223</td>\n",
       "      <td>62.712680</td>\n",
       "      <td>4.890743</td>\n",
       "      <td>4.890743</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.890743</td>\n",
       "      <td>4.890743</td>\n",
       "      <td>4.890743</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>485370.316867</td>\n",
       "      <td>6.687453e+05</td>\n",
       "      <td>6.647986e+05</td>\n",
       "      <td>6.393410e+05</td>\n",
       "      <td>6.595967e+05</td>\n",
       "      <td>9.177709e+05</td>\n",
       "      <td>6.765768e+05</td>\n",
       "      <td>468901.133269</td>\n",
       "      <td>234174.964519</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.571079</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      LIMIT_BAL       SEX  EDUCATION  MARRIAGE        AGE     PAY_0     PAY_2  \\\n",
       "0  1.236861e+06  2.519936   7.418336  3.709168  93.719507  9.703894  9.703894   \n",
       "1  4.253598e+05  1.299587   2.524677  1.262338  41.177058  1.547795  1.547795   \n",
       "2  2.500798e+05  1.035998   1.467672  0.733836  29.828164 -0.213880 -0.213880   \n",
       "3  2.773946e+05  1.077075   1.632391  0.816196  31.596725  0.060652  0.060652   \n",
       "4  7.579705e+05  1.799773        NaN  2.265223  62.712680  4.890743  4.890743   \n",
       "\n",
       "      PAY_3     PAY_4     PAY_5     PAY_6     BILL_AMT1      BILL_AMT2  \\\n",
       "0  9.703894  9.703894  9.703894  9.703894  1.178004e+06            NaN   \n",
       "1       NaN  1.547795  1.547795       NaN  2.649418e+05  352621.957687   \n",
       "2 -0.213880 -0.213880 -0.213880 -0.213880  6.772515e+04  167389.440220   \n",
       "3  0.060652  0.060652  0.060652  0.060652  9.845852e+04  196255.247953   \n",
       "4       NaN  4.890743  4.890743  4.890743           NaN            NaN   \n",
       "\n",
       "       BILL_AMT3     BILL_AMT4     BILL_AMT5     BILL_AMT6      PAY_AMT1  \\\n",
       "0            NaN  1.101620e+06  1.140599e+06  1.174860e+06  1.080050e+06   \n",
       "1  234265.111327           NaN  3.343339e+05  2.673989e+05  3.675728e+05   \n",
       "2  101937.093858  2.096570e+05  1.601847e+05  7.139200e+04  2.136813e+05   \n",
       "3  122558.500738  2.343472e+05  1.873234e+05  1.019368e+05  2.376631e+05   \n",
       "4  485370.316867  6.687453e+05  6.647986e+05  6.393410e+05  6.595967e+05   \n",
       "\n",
       "       PAY_AMT2      PAY_AMT3       PAY_AMT4       PAY_AMT5       PAY_AMT6  \\\n",
       "0  1.502795e+06  1.107854e+06  767797.819540  383447.627638  651754.019301   \n",
       "1  5.114453e+05  3.770353e+05            NaN  130498.446385  221810.961429   \n",
       "2           NaN  2.191822e+05  151904.064128   75862.748677  128945.513811   \n",
       "3  3.306873e+05  2.437813e+05  168952.470865   84376.931645  143417.250160   \n",
       "4  9.177709e+05  6.765768e+05  468901.133269  234174.964519            NaN   \n",
       "\n",
       "   p_DEFAULT_NEXT_MONTH  \n",
       "0              0.703498  \n",
       "1              0.496677  \n",
       "2              0.032246  \n",
       "3              0.013024  \n",
       "4              0.571079  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "randoms_w_miss.head(n=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <th>SEX</th>\n",
       "      <th>EDUCATION</th>\n",
       "      <th>MARRIAGE</th>\n",
       "      <th>AGE</th>\n",
       "      <th>PAY_0</th>\n",
       "      <th>PAY_2</th>\n",
       "      <th>PAY_3</th>\n",
       "      <th>PAY_4</th>\n",
       "      <th>PAY_5</th>\n",
       "      <th>PAY_6</th>\n",
       "      <th>BILL_AMT1</th>\n",
       "      <th>BILL_AMT2</th>\n",
       "      <th>BILL_AMT3</th>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <th>PAY_AMT6</th>\n",
       "      <th>p_DEFAULT_NEXT_MONTH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.236861e+06</td>\n",
       "      <td>2.519936</td>\n",
       "      <td>7.418336</td>\n",
       "      <td>3.709168</td>\n",
       "      <td>93.719507</td>\n",
       "      <td>9.703894</td>\n",
       "      <td>9.703894</td>\n",
       "      <td>9.703894</td>\n",
       "      <td>9.703894</td>\n",
       "      <td>9.703894</td>\n",
       "      <td>9.703894</td>\n",
       "      <td>1.178004e+06</td>\n",
       "      <td>1.210201e+06</td>\n",
       "      <td>846909.684010</td>\n",
       "      <td>1.101620e+06</td>\n",
       "      <td>1.140599e+06</td>\n",
       "      <td>1.174860e+06</td>\n",
       "      <td>1.080050e+06</td>\n",
       "      <td>1.502795e+06</td>\n",
       "      <td>1.107854e+06</td>\n",
       "      <td>767797.819540</td>\n",
       "      <td>383447.627638</td>\n",
       "      <td>651754.019301</td>\n",
       "      <td>0.500221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.253598e+05</td>\n",
       "      <td>1.299587</td>\n",
       "      <td>2.524677</td>\n",
       "      <td>1.262338</td>\n",
       "      <td>41.177058</td>\n",
       "      <td>1.547795</td>\n",
       "      <td>1.547795</td>\n",
       "      <td>1.547795</td>\n",
       "      <td>1.547795</td>\n",
       "      <td>1.547795</td>\n",
       "      <td>1.547795</td>\n",
       "      <td>2.649418e+05</td>\n",
       "      <td>3.526220e+05</td>\n",
       "      <td>234265.111327</td>\n",
       "      <td>3.680946e+05</td>\n",
       "      <td>3.343339e+05</td>\n",
       "      <td>2.673989e+05</td>\n",
       "      <td>3.675728e+05</td>\n",
       "      <td>5.114453e+05</td>\n",
       "      <td>3.770353e+05</td>\n",
       "      <td>261304.061796</td>\n",
       "      <td>130498.446385</td>\n",
       "      <td>221810.961429</td>\n",
       "      <td>0.443920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.500798e+05</td>\n",
       "      <td>1.035998</td>\n",
       "      <td>1.467672</td>\n",
       "      <td>0.733836</td>\n",
       "      <td>29.828164</td>\n",
       "      <td>-0.213880</td>\n",
       "      <td>-0.213880</td>\n",
       "      <td>-0.213880</td>\n",
       "      <td>-0.213880</td>\n",
       "      <td>-0.213880</td>\n",
       "      <td>-0.213880</td>\n",
       "      <td>6.772515e+04</td>\n",
       "      <td>1.673894e+05</td>\n",
       "      <td>101937.093858</td>\n",
       "      <td>2.096570e+05</td>\n",
       "      <td>1.601847e+05</td>\n",
       "      <td>7.139200e+04</td>\n",
       "      <td>2.136813e+05</td>\n",
       "      <td>2.973188e+05</td>\n",
       "      <td>2.191822e+05</td>\n",
       "      <td>151904.064128</td>\n",
       "      <td>75862.748677</td>\n",
       "      <td>128945.513811</td>\n",
       "      <td>0.011485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.773946e+05</td>\n",
       "      <td>1.077075</td>\n",
       "      <td>1.632391</td>\n",
       "      <td>0.816196</td>\n",
       "      <td>31.596725</td>\n",
       "      <td>0.060652</td>\n",
       "      <td>0.060652</td>\n",
       "      <td>0.060652</td>\n",
       "      <td>0.060652</td>\n",
       "      <td>0.060652</td>\n",
       "      <td>0.060652</td>\n",
       "      <td>9.845852e+04</td>\n",
       "      <td>1.962552e+05</td>\n",
       "      <td>122558.500738</td>\n",
       "      <td>2.343472e+05</td>\n",
       "      <td>1.873234e+05</td>\n",
       "      <td>1.019368e+05</td>\n",
       "      <td>2.376631e+05</td>\n",
       "      <td>3.306873e+05</td>\n",
       "      <td>2.437813e+05</td>\n",
       "      <td>168952.470865</td>\n",
       "      <td>84376.931645</td>\n",
       "      <td>143417.250160</td>\n",
       "      <td>0.013024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.579705e+05</td>\n",
       "      <td>1.799773</td>\n",
       "      <td>4.530446</td>\n",
       "      <td>2.265223</td>\n",
       "      <td>62.712680</td>\n",
       "      <td>4.890743</td>\n",
       "      <td>4.890743</td>\n",
       "      <td>4.890743</td>\n",
       "      <td>4.890743</td>\n",
       "      <td>4.890743</td>\n",
       "      <td>4.890743</td>\n",
       "      <td>6.391795e+05</td>\n",
       "      <td>7.041186e+05</td>\n",
       "      <td>485370.316867</td>\n",
       "      <td>6.687453e+05</td>\n",
       "      <td>6.647986e+05</td>\n",
       "      <td>6.393410e+05</td>\n",
       "      <td>6.595967e+05</td>\n",
       "      <td>9.177709e+05</td>\n",
       "      <td>6.765768e+05</td>\n",
       "      <td>468901.133269</td>\n",
       "      <td>234174.964519</td>\n",
       "      <td>398032.125757</td>\n",
       "      <td>0.496527</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      LIMIT_BAL       SEX  EDUCATION  MARRIAGE        AGE     PAY_0     PAY_2  \\\n",
       "0  1.236861e+06  2.519936   7.418336  3.709168  93.719507  9.703894  9.703894   \n",
       "1  4.253598e+05  1.299587   2.524677  1.262338  41.177058  1.547795  1.547795   \n",
       "2  2.500798e+05  1.035998   1.467672  0.733836  29.828164 -0.213880 -0.213880   \n",
       "3  2.773946e+05  1.077075   1.632391  0.816196  31.596725  0.060652  0.060652   \n",
       "4  7.579705e+05  1.799773   4.530446  2.265223  62.712680  4.890743  4.890743   \n",
       "\n",
       "      PAY_3     PAY_4     PAY_5     PAY_6     BILL_AMT1     BILL_AMT2  \\\n",
       "0  9.703894  9.703894  9.703894  9.703894  1.178004e+06  1.210201e+06   \n",
       "1  1.547795  1.547795  1.547795  1.547795  2.649418e+05  3.526220e+05   \n",
       "2 -0.213880 -0.213880 -0.213880 -0.213880  6.772515e+04  1.673894e+05   \n",
       "3  0.060652  0.060652  0.060652  0.060652  9.845852e+04  1.962552e+05   \n",
       "4  4.890743  4.890743  4.890743  4.890743  6.391795e+05  7.041186e+05   \n",
       "\n",
       "       BILL_AMT3     BILL_AMT4     BILL_AMT5     BILL_AMT6      PAY_AMT1  \\\n",
       "0  846909.684010  1.101620e+06  1.140599e+06  1.174860e+06  1.080050e+06   \n",
       "1  234265.111327  3.680946e+05  3.343339e+05  2.673989e+05  3.675728e+05   \n",
       "2  101937.093858  2.096570e+05  1.601847e+05  7.139200e+04  2.136813e+05   \n",
       "3  122558.500738  2.343472e+05  1.873234e+05  1.019368e+05  2.376631e+05   \n",
       "4  485370.316867  6.687453e+05  6.647986e+05  6.393410e+05  6.595967e+05   \n",
       "\n",
       "       PAY_AMT2      PAY_AMT3       PAY_AMT4       PAY_AMT5       PAY_AMT6  \\\n",
       "0  1.502795e+06  1.107854e+06  767797.819540  383447.627638  651754.019301   \n",
       "1  5.114453e+05  3.770353e+05  261304.061796  130498.446385  221810.961429   \n",
       "2  2.973188e+05  2.191822e+05  151904.064128   75862.748677  128945.513811   \n",
       "3  3.306873e+05  2.437813e+05  168952.470865   84376.931645  143417.250160   \n",
       "4  9.177709e+05  6.765768e+05  468901.133269  234174.964519  398032.125757   \n",
       "\n",
       "   p_DEFAULT_NEXT_MONTH  \n",
       "0              0.500221  \n",
       "1              0.443920  \n",
       "2              0.011485  \n",
       "3              0.013024  \n",
       "4              0.496527  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "randoms_wo_miss.head(n=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot ranked predictions with a reference line\n",
    "The predictions of the model on the random attack dataset are ranked from lowest to highest and plotted in two dimensions, with the x-axis simply being the ranked row index. This technique allows large amounts of information to be summarized in just two dimensions. The ranked predictions are compared to a linearly increasing reference line."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff711a56ba8>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 6)) # init plot\n",
    "\n",
    "# 45-degree reference line\n",
    "_ = ax.plot(np.linspace(*[0, N_]), np.linspace(*[0, 1]), c='grey', linestyle='-')\n",
    "\n",
    "# sorted preds w/ missing\n",
    "_ = randoms_w_miss.sort_values(by=yhat).reset_index().plot(y=yhat, ax=ax,\n",
    "                                                           title='Ranked Predictions on Random Data',\n",
    "                                                           color='royalblue',\n",
    "                                                           label='33% Missing Data')\n",
    "\n",
    "# sorted preds w/o missing\n",
    "_ = randoms_wo_miss.sort_values(by=yhat).reset_index().plot(y=yhat, ax=ax,\n",
    "                                                            label='0% Missing Data',\n",
    "                                                            color='deeppink')\n",
    "# margins and axes decoration\n",
    "_ = ax.margins(x=0, y=0) \n",
    "_ = ax.get_xaxis().set_ticks([])\n",
    "_ = ax.set_xlabel('Ranked Row Index')\n",
    "_ = ax.set_ylabel('Predicted Probability')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These results confirm the model treats customers with missing data quite differently than those without missing data. Missing values appear to increase output probabilities for low and high predicted probabilities, but seem to decrease model output for medium range predictions relative to rows without missing data. If missing data were to be allowed in credit applications, or could be hacked into the process, missingness could be used in an adversarial attack to alter the model's predictions. Also, if missingness was to somehow become more common in future data, that would have a notable impact on future model predictions. \n",
    "\n",
    "Another interesting result of the random attack is that adversaries that can force the model to generate nearly any predicted probability are now known. So, aside from general observations regarding missing values, the adversarial examples of interest seem to be on the extreme low side for both missing and non-missing cases, in the middle range of model output for rows without missing data, and the in the extreme high range of rows with missing data. A few examples of random adversaries are displayed below."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Low-range non-missing random adversarial examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <th>SEX</th>\n",
       "      <th>EDUCATION</th>\n",
       "      <th>MARRIAGE</th>\n",
       "      <th>AGE</th>\n",
       "      <th>PAY_0</th>\n",
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       "      <th>PAY_3</th>\n",
       "      <th>PAY_4</th>\n",
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       "      <th>PAY_6</th>\n",
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       "      <th>BILL_AMT2</th>\n",
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       "      <th>PAY_AMT3</th>\n",
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       "      <th>PAY_AMT5</th>\n",
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       "      <td>185999.575336</td>\n",
       "      <td>128906.897330</td>\n",
       "      <td>64377.682131</td>\n",
       "      <td>109424.103993</td>\n",
       "      <td>0.003226</td>\n",
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      ],
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       "            LIMIT_BAL       SEX  EDUCATION  MARRIAGE        AGE     PAY_0  \\\n",
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       "\n",
       "           PAY_2     PAY_3     PAY_4     PAY_5     PAY_6     BILL_AMT1  \\\n",
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       "\n",
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       "             PAY_AMT4      PAY_AMT5       PAY_AMT6  p_DEFAULT_NEXT_MONTH  \n",
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     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "randoms_wo_miss.sort_values(by=yhat).head(n=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Low-range random adversarial examples with missingness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
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       "            LIMIT_BAL       SEX  EDUCATION  MARRIAGE  AGE  PAY_0  PAY_2  \\\n",
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       "585563  252037.649816  1.038943        NaN  0.739739  NaN    NaN    NaN   \n",
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       "\n",
       "        PAY_3     PAY_4  PAY_5  PAY_6      BILL_AMT1      BILL_AMT2  \\\n",
       "35709     NaN       NaN    NaN    NaN   80480.679620  179369.860421   \n",
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     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "randoms_w_miss.sort_values(by=yhat).head(n=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Mid-range non-missing random adversarial examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
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     "execution_count": 38,
     "metadata": {},
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   "source": [
    "randoms_wo_miss[(randoms_wo_miss[yhat] > 0.3) & (randoms_wo_miss[yhat] < 0.5)].sort_values(by=yhat).head(n=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
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       "      <td>303594.143623</td>\n",
       "      <td>151618.630809</td>\n",
       "      <td>257709.384302</td>\n",
       "      <td>0.497614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32798</th>\n",
       "      <td>493270.105312</td>\n",
       "      <td>1.401712</td>\n",
       "      <td>2.934202</td>\n",
       "      <td>1.467101</td>\n",
       "      <td>45.574063</td>\n",
       "      <td>2.230337</td>\n",
       "      <td>2.230337</td>\n",
       "      <td>2.230337</td>\n",
       "      <td>2.230337</td>\n",
       "      <td>2.230337</td>\n",
       "      <td>2.230337</td>\n",
       "      <td>341351.265959</td>\n",
       "      <td>424388.283284</td>\n",
       "      <td>285534.163419</td>\n",
       "      <td>429479.572886</td>\n",
       "      <td>401806.039704</td>\n",
       "      <td>343339.671827</td>\n",
       "      <td>427196.330299</td>\n",
       "      <td>594406.229721</td>\n",
       "      <td>438193.719208</td>\n",
       "      <td>303689.901821</td>\n",
       "      <td>151666.453625</td>\n",
       "      <td>257790.669752</td>\n",
       "      <td>0.497614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473196</th>\n",
       "      <td>493097.658017</td>\n",
       "      <td>1.401453</td>\n",
       "      <td>2.933162</td>\n",
       "      <td>1.466581</td>\n",
       "      <td>45.562898</td>\n",
       "      <td>2.228603</td>\n",
       "      <td>2.228603</td>\n",
       "      <td>2.228603</td>\n",
       "      <td>2.228603</td>\n",
       "      <td>2.228603</td>\n",
       "      <td>2.228603</td>\n",
       "      <td>341157.236530</td>\n",
       "      <td>424206.044323</td>\n",
       "      <td>285403.973964</td>\n",
       "      <td>429323.695786</td>\n",
       "      <td>401634.705023</td>\n",
       "      <td>343146.832590</td>\n",
       "      <td>427044.925906</td>\n",
       "      <td>594195.563786</td>\n",
       "      <td>438038.417185</td>\n",
       "      <td>303582.269845</td>\n",
       "      <td>151612.700899</td>\n",
       "      <td>257699.305109</td>\n",
       "      <td>0.497614</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            LIMIT_BAL       SEX  EDUCATION  MARRIAGE        AGE     PAY_0  \\\n",
       "802206  493116.682111  1.401481   2.933277  1.466638  45.564129  2.228795   \n",
       "32798   493270.105312  1.401712   2.934202  1.467101  45.574063  2.230337   \n",
       "473196  493097.658017  1.401453   2.933162  1.466581  45.562898  2.228603   \n",
       "\n",
       "           PAY_2     PAY_3     PAY_4     PAY_5     PAY_6      BILL_AMT1  \\\n",
       "802206  2.228795  2.228795  2.228795  2.228795  2.228795  341178.641529   \n",
       "32798   2.230337  2.230337  2.230337  2.230337  2.230337  341351.265959   \n",
       "473196  2.228603  2.228603  2.228603  2.228603  2.228603  341157.236530   \n",
       "\n",
       "            BILL_AMT2      BILL_AMT3      BILL_AMT4      BILL_AMT5  \\\n",
       "802206  424226.148617  285418.336245  429340.891885  401653.606376   \n",
       "32798   424388.283284  285534.163419  429479.572886  401806.039704   \n",
       "473196  424206.044323  285403.973964  429323.695786  401634.705023   \n",
       "\n",
       "            BILL_AMT6       PAY_AMT1       PAY_AMT2       PAY_AMT3  \\\n",
       "802206  343168.106289  427061.628583  594218.804096  438055.549842   \n",
       "32798   343339.671827  427196.330299  594406.229721  438193.719208   \n",
       "473196  343146.832590  427044.925906  594195.563786  438038.417185   \n",
       "\n",
       "             PAY_AMT4       PAY_AMT5       PAY_AMT6  p_DEFAULT_NEXT_MONTH  \n",
       "802206  303594.143623  151618.630809  257709.384302              0.497614  \n",
       "32798   303689.901821  151666.453625  257790.669752              0.497614  \n",
       "473196  303582.269845  151612.700899  257699.305109              0.497614  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "randoms_wo_miss[(randoms_wo_miss[yhat] > 0.3) & (randoms_wo_miss[yhat] < 0.5)].sort_values(by=yhat).tail(n=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### High-range random adversarial examples with missingness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LIMIT_BAL</th>\n",
       "      <th>SEX</th>\n",
       "      <th>EDUCATION</th>\n",
       "      <th>MARRIAGE</th>\n",
       "      <th>AGE</th>\n",
       "      <th>PAY_0</th>\n",
       "      <th>PAY_2</th>\n",
       "      <th>PAY_3</th>\n",
       "      <th>PAY_4</th>\n",
       "      <th>PAY_5</th>\n",
       "      <th>PAY_6</th>\n",
       "      <th>BILL_AMT1</th>\n",
       "      <th>BILL_AMT2</th>\n",
       "      <th>BILL_AMT3</th>\n",
       "      <th>BILL_AMT4</th>\n",
       "      <th>BILL_AMT5</th>\n",
       "      <th>BILL_AMT6</th>\n",
       "      <th>PAY_AMT1</th>\n",
       "      <th>PAY_AMT2</th>\n",
       "      <th>PAY_AMT3</th>\n",
       "      <th>PAY_AMT4</th>\n",
       "      <th>PAY_AMT5</th>\n",
       "      <th>PAY_AMT6</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>994580</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.218071</td>\n",
       "      <td>6.207844</td>\n",
       "      <td>3.103922</td>\n",
       "      <td>80.722639</td>\n",
       "      <td>7.686406</td>\n",
       "      <td>7.686406</td>\n",
       "      <td>7.686406</td>\n",
       "      <td>7.686406</td>\n",
       "      <td>7.686406</td>\n",
       "      <td>7.686406</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>695366.301520</td>\n",
       "      <td>NaN</td>\n",
       "      <td>941162.00143</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>642511.836964</td>\n",
       "      <td>320878.274649</td>\n",
       "      <td>545403.570488</td>\n",
       "      <td>0.993020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>799516</th>\n",
       "      <td>1.288654e+06</td>\n",
       "      <td>2.597823</td>\n",
       "      <td>7.730665</td>\n",
       "      <td>3.865333</td>\n",
       "      <td>97.072934</td>\n",
       "      <td>10.224442</td>\n",
       "      <td>10.224442</td>\n",
       "      <td>10.224442</td>\n",
       "      <td>10.224442</td>\n",
       "      <td>10.224442</td>\n",
       "      <td>10.224442</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>886010.624324</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.566067e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>800123.874604</td>\n",
       "      <td>NaN</td>\n",
       "      <td>679194.363334</td>\n",
       "      <td>0.993734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>707572</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.356426</td>\n",
       "      <td>3.678213</td>\n",
       "      <td>93.054784</td>\n",
       "      <td>9.600710</td>\n",
       "      <td>9.600710</td>\n",
       "      <td>9.600710</td>\n",
       "      <td>9.600710</td>\n",
       "      <td>9.600710</td>\n",
       "      <td>9.600710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>839159.016062</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.490254e+06</td>\n",
       "      <td>1.098609e+06</td>\n",
       "      <td>761390.083132</td>\n",
       "      <td>380247.525656</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.994000</td>\n",
       "    </tr>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "           LIMIT_BAL       SEX  EDUCATION  MARRIAGE        AGE      PAY_0  \\\n",
       "994580           NaN  2.218071   6.207844  3.103922  80.722639   7.686406   \n",
       "799516  1.288654e+06  2.597823   7.730665  3.865333  97.072934  10.224442   \n",
       "707572           NaN       NaN   7.356426  3.678213  93.054784   9.600710   \n",
       "\n",
       "            PAY_2      PAY_3      PAY_4      PAY_5      PAY_6  BILL_AMT1  \\\n",
       "994580   7.686406   7.686406   7.686406   7.686406   7.686406        NaN   \n",
       "799516  10.224442  10.224442  10.224442  10.224442  10.224442        NaN   \n",
       "707572   9.600710   9.600710   9.600710   9.600710   9.600710        NaN   \n",
       "\n",
       "        BILL_AMT2      BILL_AMT3  BILL_AMT4     BILL_AMT5  BILL_AMT6  \\\n",
       "994580        NaN  695366.301520        NaN  941162.00143        NaN   \n",
       "799516        NaN  886010.624324        NaN           NaN        NaN   \n",
       "707572        NaN  839159.016062        NaN           NaN        NaN   \n",
       "\n",
       "        PAY_AMT1      PAY_AMT2      PAY_AMT3       PAY_AMT4       PAY_AMT5  \\\n",
       "994580       NaN           NaN           NaN  642511.836964  320878.274649   \n",
       "799516       NaN  1.566067e+06           NaN  800123.874604            NaN   \n",
       "707572       NaN  1.490254e+06  1.098609e+06  761390.083132  380247.525656   \n",
       "\n",
       "             PAY_AMT6  p_DEFAULT_NEXT_MONTH  \n",
       "994580  545403.570488              0.993020  \n",
       "799516  679194.363334              0.993734  \n",
       "707572            NaN              0.994000  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "randoms_w_miss.sort_values(by=yhat).tail(n=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Any of the above values could be used in an adversarial integrity or DOS attack and should potentially be monitored for after the model is deployed. These values could also be used to find non-sensical, non-robust interactions that can cause unwanted model behavior. If these interactions can be isolated, they can be potentially remediated from model mechanisms, potentially by editing the final model artifact or by injection of missing values or regularization during training or missing value injection based on assertions during scoring.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Conclusion\n",
    "\n",
    "In this model debugging exercise several accuracy, drift, and security patterns were discovered.\n",
    "\n",
    "\n",
    "* Monotonicity constraints held in all tested scenarios.\n",
    "\n",
    "\n",
    "* Two types of error mechanisms were identified:\n",
    "  * Over-emphasis of an important feature.\n",
    "  * Non-robust interactions.\n",
    "\n",
    "\n",
    "* In-depth analysis with partial dependence and ICE found an over-emphasis on `PAY_0`.\n",
    "\n",
    "\n",
    "* Searching for adversarial examples found:\n",
    "  * Specific features and combinations of features that can swing model predictions.\n",
    "  * Specific features and combinations of features that can reduce the residual of high-residual customers.\n",
    "  * Specific features and combinations of features that should be investigated further for disparate impact.\n",
    "  * A non-robust interaction between `PAY_0`, `PAY_3`, `PAY_AMT1` and `PAY_AMT2` in which large payment amounts do not decrease probability of default.\n",
    "  * That randomly-generated adversaries can make the model predict nearly any probability.\n",
    "  * That missing data can drastically affect model predictions.\n",
    "\n",
    "\n",
    "* To make the model more accurate, the final model artifact could be edited to remove over-emphasis on certain features or to remove model dependence on non-robust features.\n",
    "\n",
    "\n",
    "* To make the model more accurate, missing values could be injected at training time or regularization could be used to lessen the impact of overly-important features or assertions could be appended to model scoring logic to inject missing values into non-robust interactions at scoring time. \n",
    "\n",
    "\n",
    "* Assertions could be appended to model scoring logic to catch, flag, or remediate security problems in real-time, for instance by re-routing any known adversaries to a review queue or by alerting IT personnel if known adversaries are detected.\n",
    "\n",
    "\n",
    "* An autoencoder could be trained to detect random adversaries or other types of anomalies at scoring time. \n",
    "\n",
    "\n",
    "* All discovered patterns should also be considered in the context of model drift."
   ]
  }
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