{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "83708667-4fdc-1563-7b3a-06b6575d2865"
   },
   "source": [
    "\n",
    "\n",
    "# Regression-Master Template\n",
    "\n",
    "\n",
    "Template for regression and time series based predictive modelling including the model development steps.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Content"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* [1. Problem Statement](#0)\n",
    "* [2. Getting Started - Load Libraries and Dataset](#1)\n",
    "    * [2.1. Load Libraries](#1.1)    \n",
    "    * [2.2. Load Dataset](#1.2)\n",
    "* [3. Exploratory Data Analysis](#2)\n",
    "    * [3.1 Descriptive Statistics](#2.1)    \n",
    "    * [3.2. Data Visualisation](#2.2)\n",
    "* [4. Data Preparation](#3)\n",
    "    * [4.1 Data Cleaning](#3.1)\n",
    "    * [4.3.Feature Selection](#3.2)\n",
    "    * [4.3.Data Transformation](#3.3) \n",
    "        * [4.3.1 Rescaling ](#3.3.1)\n",
    "        * [4.3.2 Standardization](#3.3.2)\n",
    "        * [4.3.3 Normalization](#3.3.3)    \n",
    "* [5.Evaluate Algorithms and Models](#4)        \n",
    "    * [5.1. Train/Test Split](#4.1)\n",
    "    * [5.2. Test Options and Evaluation Metrics](#4.2)\n",
    "    * [5.3. Compare Models and Algorithms](#4.3)\n",
    "        * [5.3.1 Common Regression Models](#4.3.1)\n",
    "        * [5.3.2 Ensemble Models](#4.3.2)\n",
    "        * [5.3.3 Deep Learning Models](#4.3.3)  \n",
    "    * [5.4. Time Series based Models-ARIMA and LSTM](#4.4)\n",
    "        * [5.4.1 ARIMA Model](#4.4.1)\n",
    "        * [5.4.2 LSTM Model](#4.4.2) \n",
    "* [6. Model Tuning and Grid Search](#5)\n",
    "    * [6.1 Common Regression, Ensemble and DeepNNRegressor Grid Search](#5.1)\n",
    "    * [6.2 ARIMA and LSTM Grid Search](#5.2) \n",
    "* [7. Finalize the Model](#6)  \n",
    "    * [7.1. Results on test dataset](#6.1)\n",
    "    * [7.1. Variable Intuition/Feature Selection](#6.2) \n",
    "    * [7.3. Save model for later use](#6.3)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='0'></a>\n",
    "# 1. Problem Statement"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our goal in this jupyter notebook is to under the following. A sample problem of stock price prediction in presented in this case study.\n",
    "- How to work through a predictive modeling problem end-to-end. This notebook is applicable both for regression and classification problems.\n",
    "- How to use data transforms to improve model performance.\n",
    "- How to use algorithm tuning to improve model performance.\n",
    "- How to use ensemble methods and tuning of ensemble methods to improve model performance.\n",
    "- How to use deep Learning methods.\n",
    "- Following Models are implemented\n",
    "\n",
    "    * Linear Regression\n",
    "    * Lasso\n",
    "    * Elastic Net \n",
    "    * KNN\n",
    "    * Decision Tree (CART)\n",
    "    * Support Vector Machine \n",
    "    * Ada Boost\n",
    "    * Gradient Boosting Method\n",
    "    * Random Forest\n",
    "    * Extra Trees\n",
    "    * Neural Network - Shallow - Using sklearn\n",
    "    * Deep Neural Network - Using Keras\n",
    "- Time Series Models\n",
    "    * ARIMA Model\n",
    "    * LSTM - Using Keras\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='1'></a>\n",
    "# 2. Getting Started- Loading the data and python packages"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='1.1'></a>\n",
    "## 2.1. Loading the python packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "5d8fee34-f454-2642-8b06-ed719f0317e1"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "# Load libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pandas_datareader.data as web\n",
    "from matplotlib import pyplot\n",
    "from pandas.plotting import scatter_matrix\n",
    "import seaborn as sns\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.model_selection import KFold\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.linear_model import Lasso\n",
    "from sklearn.linear_model import ElasticNet\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.neighbors import KNeighborsRegressor\n",
    "from sklearn.svm import SVR\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.ensemble import GradientBoostingRegressor\n",
    "from sklearn.ensemble import ExtraTreesRegressor\n",
    "from sklearn.ensemble import AdaBoostRegressor\n",
    "from sklearn.neural_network import MLPRegressor\n",
    "\n",
    "#Libraries for Deep Learning Models\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense\n",
    "from keras.optimizers import SGD\n",
    "from keras.layers import LSTM\n",
    "from keras.wrappers.scikit_learn import KerasRegressor\n",
    "\n",
    "#Libraries for Statistical Models\n",
    "import statsmodels.api as sm\n",
    "\n",
    "#Libraries for Saving the Model\n",
    "from pickle import dump\n",
    "from pickle import load"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='1.2'></a>\n",
    "## 2.2. Loading the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_cell_guid": "787e35f7-bf9e-0969-8d13-a54fa87f3519"
   },
   "outputs": [],
   "source": [
    "# Get the data by webscapping using pandas datareader\n",
    "return_period = 21\n",
    "\n",
    "\n",
    "stk_tickers = ['MSFT', 'IBM', 'GOOGL']\n",
    "ccy_tickers = ['DEXJPUS', 'DEXUSUK']\n",
    "idx_tickers = ['SP500', 'DJIA', 'VIXCLS']\n",
    "\n",
    "stk_data = web.DataReader(stk_tickers, 'yahoo')\n",
    "ccy_data = web.DataReader(ccy_tickers, 'fred')\n",
    "idx_data = web.DataReader(idx_tickers, 'fred')\n",
    "\n",
    "Y = np.log(stk_data.loc[:, ('Adj Close', 'MSFT')]).diff(return_period).shift(-return_period)\n",
    "Y.name = Y.name[-1]+'_pred'\n",
    "\n",
    "X1 = np.log(stk_data.loc[:, ('Adj Close', ('GOOGL', 'IBM'))]).diff(return_period)\n",
    "X1.columns = X1.columns.droplevel()\n",
    "X2 = np.log(ccy_data).diff(return_period)\n",
    "X3 = np.log(idx_data).diff(return_period)\n",
    "\n",
    "X4 = pd.concat([Y.diff(i) for i in [21, 63, 126,252]], axis=1).dropna()\n",
    "X4.columns = ['1M', '3M', '6M', '1Y']\n",
    "\n",
    "X = pd.concat([X1, X2, X3, X4], axis=1)\n",
    "\n",
    "dataset = pd.concat([Y, X], axis=1).dropna()\n",
    "Y = dataset.loc[:, Y.name]\n",
    "X = dataset.loc[:, X.columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Diable the warnings\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(dataset)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Converting the data to supervised regression format\n",
    "All the predictor variables are changed to lagged variable, as the t-1 value of the lagged variable will be used for prediction. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def series_to_supervised(data, lag=1):\n",
    "    n_vars = data.shape[1]\n",
    "    df = pd.DataFrame(data)    \n",
    "    cols, names = list(), list()\n",
    "    for i in range(lag, 0, -1):\n",
    "        cols.append(df.shift(i))\n",
    "        names += [('%s(t-%d)' % (df.columns[j], i)) for j in range(n_vars)]\n",
    "    agg = pd.concat(cols, axis=1)\n",
    "    agg.columns = names\n",
    "    agg = pd.DataFrame(data.iloc[:,0]).join(agg)\n",
    "    agg.dropna(inplace=True)\n",
    "    return agg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset= series_to_supervised(dataset,1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "df6a4523-b385-69ee-c933-592826d81431"
   },
   "source": [
    "<a id='2'></a>\n",
    "# 3. Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='2.1'></a>\n",
    "## 3.1. Descriptive Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "_cell_guid": "52f85dc2-0f91-3c50-400e-ddc38bea966b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2252, 13)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# shape\n",
    "dataset.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MSFT_pred</th>\n",
       "      <th>MSFT_pred(t-1)</th>\n",
       "      <th>GOOGL(t-1)</th>\n",
       "      <th>IBM(t-1)</th>\n",
       "      <th>DEXJPUS(t-1)</th>\n",
       "      <th>DEXUSUK(t-1)</th>\n",
       "      <th>SP500(t-1)</th>\n",
       "      <th>DJIA(t-1)</th>\n",
       "      <th>VIXCLS(t-1)</th>\n",
       "      <th>1M(t-1)</th>\n",
       "      <th>3M(t-1)</th>\n",
       "      <th>6M(t-1)</th>\n",
       "      <th>1Y(t-1)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-01-04</th>\n",
       "      <td>-0.015788</td>\n",
       "      <td>-0.001431</td>\n",
       "      <td>0.055329</td>\n",
       "      <td>0.015718</td>\n",
       "      <td>-0.014243</td>\n",
       "      <td>-0.014930</td>\n",
       "      <td>0.037784</td>\n",
       "      <td>0.025045</td>\n",
       "      <td>-0.022460</td>\n",
       "      <td>-0.041166</td>\n",
       "      <td>-0.137312</td>\n",
       "      <td>-0.078563</td>\n",
       "      <td>0.076487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-05</th>\n",
       "      <td>-0.008248</td>\n",
       "      <td>-0.015788</td>\n",
       "      <td>0.049571</td>\n",
       "      <td>0.015426</td>\n",
       "      <td>-0.008988</td>\n",
       "      <td>-0.006013</td>\n",
       "      <td>0.037769</td>\n",
       "      <td>0.028544</td>\n",
       "      <td>-0.036162</td>\n",
       "      <td>-0.054624</td>\n",
       "      <td>-0.120203</td>\n",
       "      <td>-0.058879</td>\n",
       "      <td>0.090434</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            MSFT_pred  MSFT_pred(t-1)  GOOGL(t-1)  IBM(t-1)  DEXJPUS(t-1)  DEXUSUK(t-1)  \\\n",
       "2011-01-04  -0.015788       -0.001431    0.055329  0.015718     -0.014243     -0.014930   \n",
       "2011-01-05  -0.008248       -0.015788    0.049571  0.015426     -0.008988     -0.006013   \n",
       "\n",
       "            SP500(t-1)  DJIA(t-1)  VIXCLS(t-1)   1M(t-1)   3M(t-1)   6M(t-1)   1Y(t-1)  \n",
       "2011-01-04    0.037784   0.025045    -0.022460 -0.041166 -0.137312 -0.078563  0.076487  \n",
       "2011-01-05    0.037769   0.028544    -0.036162 -0.054624 -0.120203 -0.058879  0.090434  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# peek at data\n",
    "pd.set_option('display.width', 100)\n",
    "dataset.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "_cell_guid": "f36dd804-0c16-f0c9-05c9-d22b85a79e75"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MSFT_pred         float64\n",
       "MSFT_pred(t-1)    float64\n",
       "GOOGL(t-1)        float64\n",
       "IBM(t-1)          float64\n",
       "DEXJPUS(t-1)      float64\n",
       "DEXUSUK(t-1)      float64\n",
       "SP500(t-1)        float64\n",
       "DJIA(t-1)         float64\n",
       "VIXCLS(t-1)       float64\n",
       "1M(t-1)           float64\n",
       "3M(t-1)           float64\n",
       "6M(t-1)           float64\n",
       "1Y(t-1)           float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# types\n",
    "pd.set_option('display.max_rows', 500)\n",
    "dataset.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "_cell_guid": "7bffeec0-5bbc-fffb-18f2-3da56b862ca3"
   },
   "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>MSFT_pred</th>\n",
       "      <th>MSFT_pred(t-1)</th>\n",
       "      <th>GOOGL(t-1)</th>\n",
       "      <th>IBM(t-1)</th>\n",
       "      <th>DEXJPUS(t-1)</th>\n",
       "      <th>DEXUSUK(t-1)</th>\n",
       "      <th>SP500(t-1)</th>\n",
       "      <th>DJIA(t-1)</th>\n",
       "      <th>VIXCLS(t-1)</th>\n",
       "      <th>1M(t-1)</th>\n",
       "      <th>3M(t-1)</th>\n",
       "      <th>6M(t-1)</th>\n",
       "      <th>1Y(t-1)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2252.000</td>\n",
       "      <td>2252.000</td>\n",
       "      <td>2252.000</td>\n",
       "      <td>2252.000</td>\n",
       "      <td>2.252e+03</td>\n",
       "      <td>2.252e+03</td>\n",
       "      <td>2252.000</td>\n",
       "      <td>2252.000</td>\n",
       "      <td>2252.000</td>\n",
       "      <td>2.252e+03</td>\n",
       "      <td>2.252e+03</td>\n",
       "      <td>2252.000</td>\n",
       "      <td>2252.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.019</td>\n",
       "      <td>0.019</td>\n",
       "      <td>0.014</td>\n",
       "      <td>0.001</td>\n",
       "      <td>2.056e-03</td>\n",
       "      <td>-1.915e-03</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.007</td>\n",
       "      <td>0.005</td>\n",
       "      <td>4.086e-04</td>\n",
       "      <td>5.506e-04</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.058</td>\n",
       "      <td>0.058</td>\n",
       "      <td>0.067</td>\n",
       "      <td>0.063</td>\n",
       "      <td>2.503e-02</td>\n",
       "      <td>2.374e-02</td>\n",
       "      <td>0.043</td>\n",
       "      <td>0.045</td>\n",
       "      <td>0.265</td>\n",
       "      <td>8.737e-02</td>\n",
       "      <td>8.570e-02</td>\n",
       "      <td>0.077</td>\n",
       "      <td>0.081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-0.302</td>\n",
       "      <td>-0.302</td>\n",
       "      <td>-0.351</td>\n",
       "      <td>-0.461</td>\n",
       "      <td>-8.290e-02</td>\n",
       "      <td>-1.227e-01</td>\n",
       "      <td>-0.400</td>\n",
       "      <td>-0.444</td>\n",
       "      <td>-0.827</td>\n",
       "      <td>-4.272e-01</td>\n",
       "      <td>-3.467e-01</td>\n",
       "      <td>-0.327</td>\n",
       "      <td>-0.410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.014</td>\n",
       "      <td>-0.014</td>\n",
       "      <td>-0.028</td>\n",
       "      <td>-0.031</td>\n",
       "      <td>-1.294e-02</td>\n",
       "      <td>-1.556e-02</td>\n",
       "      <td>-0.009</td>\n",
       "      <td>-0.010</td>\n",
       "      <td>-0.148</td>\n",
       "      <td>-5.193e-02</td>\n",
       "      <td>-4.780e-02</td>\n",
       "      <td>-0.047</td>\n",
       "      <td>-0.048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.023</td>\n",
       "      <td>0.023</td>\n",
       "      <td>0.017</td>\n",
       "      <td>0.004</td>\n",
       "      <td>9.865e-04</td>\n",
       "      <td>-7.240e-04</td>\n",
       "      <td>0.014</td>\n",
       "      <td>0.012</td>\n",
       "      <td>-0.021</td>\n",
       "      <td>5.407e-05</td>\n",
       "      <td>1.940e-03</td>\n",
       "      <td>-0.002</td>\n",
       "      <td>0.004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.052</td>\n",
       "      <td>0.052</td>\n",
       "      <td>0.053</td>\n",
       "      <td>0.039</td>\n",
       "      <td>1.489e-02</td>\n",
       "      <td>1.384e-02</td>\n",
       "      <td>0.030</td>\n",
       "      <td>0.031</td>\n",
       "      <td>0.120</td>\n",
       "      <td>4.945e-02</td>\n",
       "      <td>5.187e-02</td>\n",
       "      <td>0.045</td>\n",
       "      <td>0.056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.244</td>\n",
       "      <td>0.244</td>\n",
       "      <td>0.271</td>\n",
       "      <td>0.230</td>\n",
       "      <td>1.023e-01</td>\n",
       "      <td>6.963e-02</td>\n",
       "      <td>0.203</td>\n",
       "      <td>0.214</td>\n",
       "      <td>1.799</td>\n",
       "      <td>5.407e-01</td>\n",
       "      <td>3.619e-01</td>\n",
       "      <td>0.275</td>\n",
       "      <td>0.230</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       MSFT_pred  MSFT_pred(t-1)  GOOGL(t-1)  IBM(t-1)  DEXJPUS(t-1)  DEXUSUK(t-1)  SP500(t-1)  \\\n",
       "count   2252.000        2252.000    2252.000  2252.000     2.252e+03     2.252e+03    2252.000   \n",
       "mean       0.019           0.019       0.014     0.001     2.056e-03    -1.915e-03       0.008   \n",
       "std        0.058           0.058       0.067     0.063     2.503e-02     2.374e-02       0.043   \n",
       "min       -0.302          -0.302      -0.351    -0.461    -8.290e-02    -1.227e-01      -0.400   \n",
       "25%       -0.014          -0.014      -0.028    -0.031    -1.294e-02    -1.556e-02      -0.009   \n",
       "50%        0.023           0.023       0.017     0.004     9.865e-04    -7.240e-04       0.014   \n",
       "75%        0.052           0.052       0.053     0.039     1.489e-02     1.384e-02       0.030   \n",
       "max        0.244           0.244       0.271     0.230     1.023e-01     6.963e-02       0.203   \n",
       "\n",
       "       DJIA(t-1)  VIXCLS(t-1)    1M(t-1)    3M(t-1)   6M(t-1)   1Y(t-1)  \n",
       "count   2252.000     2252.000  2.252e+03  2.252e+03  2252.000  2252.000  \n",
       "mean       0.007        0.005  4.086e-04  5.506e-04     0.001     0.004  \n",
       "std        0.045        0.265  8.737e-02  8.570e-02     0.077     0.081  \n",
       "min       -0.444       -0.827 -4.272e-01 -3.467e-01    -0.327    -0.410  \n",
       "25%       -0.010       -0.148 -5.193e-02 -4.780e-02    -0.047    -0.048  \n",
       "50%        0.012       -0.021  5.407e-05  1.940e-03    -0.002     0.004  \n",
       "75%        0.031        0.120  4.945e-02  5.187e-02     0.045     0.056  \n",
       "max        0.214        1.799  5.407e-01  3.619e-01     0.275     0.230  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# describe data\n",
    "pd.set_option('precision', 3)\n",
    "dataset.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='2.2'></a>\n",
    "## 3.2. Data Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "_cell_guid": "16d50177-f93e-9d26-af7a-313d7ebe9fcf"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# histograms\n",
    "dataset.hist(sharex=False, sharey=False, xlabelsize=1, ylabelsize=1, figsize=(12,12))\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "_cell_guid": "ca420570-fce1-e2ff-8511-50691e099d69"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# density\n",
    "dataset.plot(kind='density', subplots=True, layout=(4,4), sharex=False, legend=True, fontsize=1, figsize=(15,15))\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Box and Whisker Plots\n",
    "dataset.plot(kind='box', subplots=True, layout=(4,4), sharex=False, sharey=False, figsize=(15,15))\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x21b92b917b8>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# correlation\n",
    "correlation = dataset.corr()\n",
    "pyplot.figure(figsize=(15,15))\n",
    "pyplot.title('Correlation Matrix')\n",
    "sns.heatmap(correlation, vmax=1, square=True,annot=True,cmap='cubehelix')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1080x1080 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 169 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scatterplot Matrix\n",
    "from pandas.plotting import scatter_matrix\n",
    "pyplot.figure(figsize=(15,15))\n",
    "scatter_matrix(dataset,figsize=(12,12))\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='2.3'></a>\n",
    "## 3.3. Time Series Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Time series broken down into different time series comonent "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Y= dataset[\"MSFT_pred\"]\n",
    "res = sm.tsa.seasonal_decompose(Y,freq=365)\n",
    "fig = res.plot()\n",
    "fig.set_figheight(8)\n",
    "fig.set_figwidth(15)\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='3'></a>\n",
    "## 4. Data Preparation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='3.1'></a>\n",
    "## 4.1. Data Cleaning\n",
    "Check for the NAs in the rows, either drop them or fill them with the mean of the column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Null Values = False\n"
     ]
    }
   ],
   "source": [
    "#Checking for any null values and removing the null values'''\n",
    "print('Null Values =',dataset.isnull().values.any())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Given that there are null values drop the rown contianing the null values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop the rows containing NA\n",
    "#dataset.dropna(axis=0)\n",
    "# Fill na with 0\n",
    "#dataset.fillna('0')\n",
    "\n",
    "#Filling the NAs with the mean of the column.\n",
    "#dataset['col'] = dataset['col'].fillna(dataset['col'].mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='3.3'></a>\n",
    "## 4.3. Feature Selection\n",
    "Statistical tests can be used to select those features that have the strongest relationship with the output variable.The scikit-learn library provides the SelectKBest class that can be used with a suite of different statistical tests to select a specific number of features.\n",
    "The example below uses the chi-squared (chi²) statistical test for non-negative features to select 10 of the best features from the Dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SelectKBest(k=5, score_func=<function f_classif at 0x0000021B972962F0>)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.feature_selection import SelectKBest\n",
    "from sklearn.feature_selection import chi2\n",
    "\n",
    "bestfeatures = SelectKBest(k=5)\n",
    "bestfeatures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             Specs    Score\n",
      "0   MSFT_pred(t-1)  667.074\n",
      "1       GOOGL(t-1)   15.767\n",
      "10         6M(t-1)    7.466\n",
      "9          3M(t-1)    6.491\n",
      "4     DEXUSUK(t-1)    3.361\n",
      "5       SP500(t-1)    1.716\n",
      "8          1M(t-1)    1.656\n",
      "7      VIXCLS(t-1)    1.441\n",
      "11         1Y(t-1)    1.197\n",
      "6        DJIA(t-1)    1.175\n"
     ]
    }
   ],
   "source": [
    "Y= dataset[\"MSFT_pred\"]\n",
    "X = dataset.loc[:, dataset.columns != 'MSFT_pred']\n",
    "fit = bestfeatures.fit(X,Y)\n",
    "dfscores = pd.DataFrame(fit.scores_)\n",
    "dfcolumns = pd.DataFrame(X.columns)\n",
    "#concat two dataframes for better visualization \n",
    "featureScores = pd.concat([dfcolumns,dfscores],axis=1)\n",
    "featureScores.columns = ['Specs','Score']  #naming the dataframe columns\n",
    "print(featureScores.nlargest(10,'Score'))  #print 10 best features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As it can be seen from the result above that t-1 is an important feature"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='3.4'></a>\n",
    "## 4.4. Data Transformation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='3.4.1'></a>\n",
    "### 4.4.1. Rescale Data\n",
    "When your data is comprised of attributes with varying scales, many machine learning algorithms\n",
    "can benefit from rescaling the attributes to all have the same scale. Often this is referred to\n",
    "as normalization and attributes are often rescaled into the range between 0 and 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.551</td>\n",
       "      <td>0.653</td>\n",
       "      <td>0.690</td>\n",
       "      <td>0.371</td>\n",
       "      <td>0.560</td>\n",
       "      <td>0.726</td>\n",
       "      <td>0.713</td>\n",
       "      <td>0.306</td>\n",
       "      <td>0.399</td>\n",
       "      <td>0.296</td>\n",
       "      <td>0.413</td>\n",
       "      <td>0.760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.525</td>\n",
       "      <td>0.644</td>\n",
       "      <td>0.689</td>\n",
       "      <td>0.399</td>\n",
       "      <td>0.607</td>\n",
       "      <td>0.726</td>\n",
       "      <td>0.719</td>\n",
       "      <td>0.301</td>\n",
       "      <td>0.385</td>\n",
       "      <td>0.320</td>\n",
       "      <td>0.446</td>\n",
       "      <td>0.781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.538</td>\n",
       "      <td>0.648</td>\n",
       "      <td>0.687</td>\n",
       "      <td>0.459</td>\n",
       "      <td>0.537</td>\n",
       "      <td>0.734</td>\n",
       "      <td>0.723</td>\n",
       "      <td>0.294</td>\n",
       "      <td>0.389</td>\n",
       "      <td>0.329</td>\n",
       "      <td>0.454</td>\n",
       "      <td>0.773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.514</td>\n",
       "      <td>0.635</td>\n",
       "      <td>0.713</td>\n",
       "      <td>0.382</td>\n",
       "      <td>0.538</td>\n",
       "      <td>0.724</td>\n",
       "      <td>0.718</td>\n",
       "      <td>0.307</td>\n",
       "      <td>0.347</td>\n",
       "      <td>0.331</td>\n",
       "      <td>0.418</td>\n",
       "      <td>0.753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.533</td>\n",
       "      <td>0.633</td>\n",
       "      <td>0.696</td>\n",
       "      <td>0.395</td>\n",
       "      <td>0.580</td>\n",
       "      <td>0.715</td>\n",
       "      <td>0.716</td>\n",
       "      <td>0.312</td>\n",
       "      <td>0.379</td>\n",
       "      <td>0.350</td>\n",
       "      <td>0.509</td>\n",
       "      <td>0.764</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      0      1      2      3      4      5      6      7      8      9      10     11\n",
       "0  0.551  0.653  0.690  0.371  0.560  0.726  0.713  0.306  0.399  0.296  0.413  0.760\n",
       "1  0.525  0.644  0.689  0.399  0.607  0.726  0.719  0.301  0.385  0.320  0.446  0.781\n",
       "2  0.538  0.648  0.687  0.459  0.537  0.734  0.723  0.294  0.389  0.329  0.454  0.773\n",
       "3  0.514  0.635  0.713  0.382  0.538  0.724  0.718  0.307  0.347  0.331  0.418  0.753\n",
       "4  0.533  0.633  0.696  0.395  0.580  0.715  0.716  0.312  0.379  0.350  0.509  0.764"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import MinMaxScaler\n",
    "scaler = MinMaxScaler(feature_range=(0, 1))\n",
    "rescaledX = pd.DataFrame(scaler.fit_transform(X))\n",
    "# summarize transformed data\n",
    "rescaledX.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='3.4.2'></a>\n",
    "### 4.4.2. Standardize Data\n",
    "Standardization is a useful technique to transform attributes with a Gaussian distribution and\n",
    "differing means and standard deviations to a standard Gaussian distribution with a mean of\n",
    "0 and a standard deviation of 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.357</td>\n",
       "      <td>0.624</td>\n",
       "      <td>0.229</td>\n",
       "      <td>-0.651</td>\n",
       "      <td>-0.548</td>\n",
       "      <td>0.695</td>\n",
       "      <td>0.408</td>\n",
       "      <td>-0.104</td>\n",
       "      <td>-0.476</td>\n",
       "      <td>-1.609</td>\n",
       "      <td>-1.041</td>\n",
       "      <td>0.889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.604</td>\n",
       "      <td>0.538</td>\n",
       "      <td>0.224</td>\n",
       "      <td>-0.441</td>\n",
       "      <td>-0.173</td>\n",
       "      <td>0.694</td>\n",
       "      <td>0.486</td>\n",
       "      <td>-0.155</td>\n",
       "      <td>-0.630</td>\n",
       "      <td>-1.409</td>\n",
       "      <td>-0.784</td>\n",
       "      <td>1.061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.474</td>\n",
       "      <td>0.570</td>\n",
       "      <td>0.203</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.740</td>\n",
       "      <td>0.797</td>\n",
       "      <td>0.552</td>\n",
       "      <td>-0.228</td>\n",
       "      <td>-0.583</td>\n",
       "      <td>-1.330</td>\n",
       "      <td>-0.719</td>\n",
       "      <td>0.999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.707</td>\n",
       "      <td>0.454</td>\n",
       "      <td>0.482</td>\n",
       "      <td>-0.565</td>\n",
       "      <td>-0.733</td>\n",
       "      <td>0.663</td>\n",
       "      <td>0.477</td>\n",
       "      <td>-0.092</td>\n",
       "      <td>-1.056</td>\n",
       "      <td>-1.315</td>\n",
       "      <td>-1.001</td>\n",
       "      <td>0.836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.526</td>\n",
       "      <td>0.439</td>\n",
       "      <td>0.299</td>\n",
       "      <td>-0.470</td>\n",
       "      <td>-0.385</td>\n",
       "      <td>0.533</td>\n",
       "      <td>0.439</td>\n",
       "      <td>-0.043</td>\n",
       "      <td>-0.695</td>\n",
       "      <td>-1.156</td>\n",
       "      <td>-0.287</td>\n",
       "      <td>0.922</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      0      1      2      3      4      5      6      7      8      9      10     11\n",
       "0 -0.357  0.624  0.229 -0.651 -0.548  0.695  0.408 -0.104 -0.476 -1.609 -1.041  0.889\n",
       "1 -0.604  0.538  0.224 -0.441 -0.173  0.694  0.486 -0.155 -0.630 -1.409 -0.784  1.061\n",
       "2 -0.474  0.570  0.203  0.004 -0.740  0.797  0.552 -0.228 -0.583 -1.330 -0.719  0.999\n",
       "3 -0.707  0.454  0.482 -0.565 -0.733  0.663  0.477 -0.092 -1.056 -1.315 -1.001  0.836\n",
       "4 -0.526  0.439  0.299 -0.470 -0.385  0.533  0.439 -0.043 -0.695 -1.156 -0.287  0.922"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "scaler = StandardScaler().fit(X)\n",
    "StandardisedX = pd.DataFrame(scaler.fit_transform(X))\n",
    "# summarize transformed data\n",
    "StandardisedX.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='3.4.3'></a>\n",
    "### 4.4.1. Normalize Data\n",
    "Normalizing in scikit-learn refers to rescaling each observation (row) to have a length of 1 (called\n",
    "a unit norm or a vector with the length of 1 in linear algebra)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.007</td>\n",
       "      <td>0.281</td>\n",
       "      <td>0.080</td>\n",
       "      <td>-0.072</td>\n",
       "      <td>-0.076</td>\n",
       "      <td>0.192</td>\n",
       "      <td>0.127</td>\n",
       "      <td>-0.114</td>\n",
       "      <td>-0.209</td>\n",
       "      <td>-0.696</td>\n",
       "      <td>-0.398</td>\n",
       "      <td>0.388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.084</td>\n",
       "      <td>0.262</td>\n",
       "      <td>0.082</td>\n",
       "      <td>-0.048</td>\n",
       "      <td>-0.032</td>\n",
       "      <td>0.200</td>\n",
       "      <td>0.151</td>\n",
       "      <td>-0.191</td>\n",
       "      <td>-0.289</td>\n",
       "      <td>-0.636</td>\n",
       "      <td>-0.312</td>\n",
       "      <td>0.479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.044</td>\n",
       "      <td>0.277</td>\n",
       "      <td>0.076</td>\n",
       "      <td>0.012</td>\n",
       "      <td>-0.104</td>\n",
       "      <td>0.226</td>\n",
       "      <td>0.169</td>\n",
       "      <td>-0.297</td>\n",
       "      <td>-0.271</td>\n",
       "      <td>-0.608</td>\n",
       "      <td>-0.289</td>\n",
       "      <td>0.458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.111</td>\n",
       "      <td>0.224</td>\n",
       "      <td>0.162</td>\n",
       "      <td>-0.062</td>\n",
       "      <td>-0.099</td>\n",
       "      <td>0.186</td>\n",
       "      <td>0.144</td>\n",
       "      <td>-0.099</td>\n",
       "      <td>-0.469</td>\n",
       "      <td>-0.573</td>\n",
       "      <td>-0.386</td>\n",
       "      <td>0.369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.072</td>\n",
       "      <td>0.275</td>\n",
       "      <td>0.129</td>\n",
       "      <td>-0.062</td>\n",
       "      <td>-0.071</td>\n",
       "      <td>0.197</td>\n",
       "      <td>0.170</td>\n",
       "      <td>-0.041</td>\n",
       "      <td>-0.387</td>\n",
       "      <td>-0.632</td>\n",
       "      <td>-0.134</td>\n",
       "      <td>0.508</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      0      1      2      3      4      5      6      7      8      9      10     11\n",
       "0 -0.007  0.281  0.080 -0.072 -0.076  0.192  0.127 -0.114 -0.209 -0.696 -0.398  0.388\n",
       "1 -0.084  0.262  0.082 -0.048 -0.032  0.200  0.151 -0.191 -0.289 -0.636 -0.312  0.479\n",
       "2 -0.044  0.277  0.076  0.012 -0.104  0.226  0.169 -0.297 -0.271 -0.608 -0.289  0.458\n",
       "3 -0.111  0.224  0.162 -0.062 -0.099  0.186  0.144 -0.099 -0.469 -0.573 -0.386  0.369\n",
       "4 -0.072  0.275  0.129 -0.062 -0.071  0.197  0.170 -0.041 -0.387 -0.632 -0.134  0.508"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import Normalizer\n",
    "scaler = Normalizer().fit(X)\n",
    "NormalizedX = pd.DataFrame(scaler.fit_transform(X))\n",
    "# summarize transformed data\n",
    "NormalizedX.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='4'></a>\n",
    "# 5. Evaluate Algorithms and Models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='4.1'></a>\n",
    "## 5.1. Train Test Split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# split out validation dataset for the end\n",
    "\n",
    "validation_size = 0.2\n",
    "\n",
    "#In case the data is not dependent on the time series, then train and test split randomly\n",
    "seed = 7\n",
    "# X_train, X_validation, Y_train, Y_validation = train_test_split(X, Y, test_size=validation_size, random_state=seed)\n",
    "\n",
    "#In case the data is not dependent on the time series, then train and test split should be done based on sequential sample\n",
    "#This can be done by selecting an arbitrary split point in the ordered list of observations and creating two new datasets.\n",
    "\n",
    "train_size = int(len(X) * (1-validation_size))\n",
    "X_train, X_validation = X[0:train_size], X[train_size:len(X)]\n",
    "Y_train, Y_validation = Y[0:train_size], Y[train_size:len(X)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='4.2'></a>\n",
    "## 5.2. Test Options and Evaluation Metrics\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "_cell_guid": "5702bc31-06bf-8b6a-42de-366a6b3311a8"
   },
   "outputs": [],
   "source": [
    "# test options for regression\n",
    "num_folds = 10\n",
    "scoring = 'neg_mean_squared_error'\n",
    "#scoring ='neg_mean_absolute_error'\n",
    "#scoring = 'r2'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='4.3'></a>\n",
    "## 5.3. Compare Models and Algorithms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='4.3.1'></a>\n",
    "### 5.3.1. Common Models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "_cell_guid": "772802f7-f4e4-84ee-6377-6464ab2e5da4"
   },
   "outputs": [],
   "source": [
    "# spot check the algorithms\n",
    "models = []\n",
    "models.append(('LR', LinearRegression()))\n",
    "models.append(('LASSO', Lasso()))\n",
    "models.append(('EN', ElasticNet()))\n",
    "models.append(('KNN', KNeighborsRegressor()))\n",
    "models.append(('CART', DecisionTreeRegressor()))\n",
    "models.append(('SVR', SVR()))\n",
    "#Neural Network\n",
    "models.append(('MLP', MLPRegressor()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='4.3.2'></a>\n",
    "### 5.3.2. Ensemble Models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Ensable Models \n",
    "# Boosting methods\n",
    "models.append(('ABR', AdaBoostRegressor()))\n",
    "models.append(('GBR', GradientBoostingRegressor()))\n",
    "# Bagging methods\n",
    "models.append(('RFR', RandomForestRegressor()))\n",
    "models.append(('ETR', ExtraTreesRegressor()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='4.3.3'></a>\n",
    "### 5.3.3. Deep Learning Model-NN Regressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Running deep learning models and performing cross validation takes time\n",
    "#Set the following Flag to 0 if the Deep LEarning Models Flag has to be disabled\n",
    "EnableDeepLearningRegreesorFlag = 0\n",
    "\n",
    "def create_model(neurons=12, activation='relu', learn_rate = 0.01, momentum=0):\n",
    "        # create model\n",
    "        model = Sequential()\n",
    "        model.add(Dense(neurons, input_dim=X_train.shape[1], activation=activation))\n",
    "        #The number of hidden layers can be increased\n",
    "        model.add(Dense(2, activation=activation))\n",
    "        # Final output layer\n",
    "        model.add(Dense(1, kernel_initializer='normal'))\n",
    "        # Compile model\n",
    "        optimizer = SGD(lr=learn_rate, momentum=momentum)\n",
    "        model.compile(loss='mean_squared_error', optimizer='adam')\n",
    "        return model   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Add Deep Learning Regressor\n",
    "if ( EnableDeepLearningRegreesorFlag == 1):\n",
    "    models.append(('DNN', KerasRegressor(build_fn=create_model, epochs=100, batch_size=100, verbose=1)))       \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### K-folds cross validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "_cell_guid": "a784ab4a-eb59-98cc-76cf-b55f382d057a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LR: 0.000419 (0.000159)\n",
      "LASSO: 0.003024 (0.001482)\n",
      "EN: 0.003024 (0.001482)\n",
      "KNN: 0.000934 (0.000363)\n",
      "CART: 0.000988 (0.000280)\n",
      "SVR: 0.001448 (0.000906)\n",
      "MLP: 0.000734 (0.000242)\n",
      "ABR: 0.000577 (0.000199)\n",
      "GBR: 0.000460 (0.000179)\n",
      "RFR: 0.000473 (0.000185)\n",
      "ETR: 0.000472 (0.000192)\n"
     ]
    }
   ],
   "source": [
    "results = []\n",
    "names = []\n",
    "for name, model in models:\n",
    "    kfold = KFold(n_splits=num_folds, random_state=seed)\n",
    "    #converted mean square error to positive. The lower the beter\n",
    "    cv_results = -1* cross_val_score(model, X_train, Y_train, cv=kfold, scoring=scoring)\n",
    "    results.append(cv_results)\n",
    "    names.append(name)\n",
    "    msg = \"%s: %f (%f)\" % (name, cv_results.mean(), cv_results.std())\n",
    "    print(msg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Algorithm comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "_cell_guid": "67873e9d-bc9b-6963-f594-805f1efbfbb3"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# compare algorithms\n",
    "fig = pyplot.figure()\n",
    "fig.suptitle('Algorithm Comparison')\n",
    "ax = fig.add_subplot(111)\n",
    "pyplot.boxplot(results)\n",
    "ax.set_xticklabels(names)\n",
    "fig.set_size_inches(15,8)\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The chart shows MSE. Lower the MSE, better is the model performance."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='4.4'></a>\n",
    "## 5.4. Time Series based Models- ARIMA and LSTM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='4.4.1'></a>\n",
    "### 5.4.1 Time Series Model - ARIMA Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Preparing data for the ARIMAX Model, seperating endogeneous and exogenous variables\n",
    "X_train_ARIMA=X_train.drop(['MSFT_pred(t-1)'], axis = 'columns' ).dropna()\n",
    "X_validation_ARIMA=X_validation.drop(['MSFT_pred(t-1)'], axis = 'columns' ).dropna()\n",
    "tr_len = len(X_train_ARIMA)\n",
    "te_len = len(X_validation_ARIMA)\n",
    "to_len = len (X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.tsa.arima_model import ARIMA\n",
    "#from statsmodels.tsa.statespace.sarimax import SARIMAX\n",
    "\n",
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "modelARIMA=ARIMA(endog=Y_train,exog=X_train_ARIMA,order=[1,0,0])\n",
    "#modelARIMA= SARIMAX(Y_train,order=(1,1,0),seasonal_order=[1,0,0,0],exog = X_train_ARIMA)\n",
    "\n",
    "model_fit = modelARIMA.fit()\n",
    "#print(model_fit.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0051007878797309026"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "error_Training_ARIMA = mean_squared_error(Y_train, model_fit.fittedvalues)\n",
    "predicted = model_fit.predict(start = tr_len -1 ,end = to_len -1, exog = X_validation_ARIMA)[1:]\n",
    "error_Test_ARIMA = mean_squared_error(Y_validation,predicted)\n",
    "error_Test_ARIMA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Add Cross validation if possible\n",
    "# #model = build_model(_alpha=1.0, _l1_ratio=0.3)\n",
    "# from sklearn.model_selection import TimeSeriesSplit\n",
    "# tscv = TimeSeriesSplit(n_splits=5)\n",
    "# scores = cross_val_score(modelARIMA, X_train, Y_train, cv=tscv, scoring=scoring)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='4.4.2'></a>\n",
    "### 5.4.2 LSTM Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data needs to be in 3D format for the LSTM model. So, Performing the data transform. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1801, 1, 12) (1801,) (451, 1, 12) (451,)\n"
     ]
    }
   ],
   "source": [
    "X_train_LSTM, X_validation_LSTM = np.array(X_train), np.array(X_validation)\n",
    "Y_train_LSTM, Y_validation_LSTM = np.array(Y_train), np.array(Y_validation)\n",
    "X_train_LSTM= X_train_LSTM.reshape((X_train_LSTM.shape[0], 1, X_train_LSTM.shape[1]))\n",
    "X_validation_LSTM= X_validation_LSTM.reshape((X_validation_LSTM.shape[0], 1, X_validation_LSTM.shape[1]))\n",
    "print(X_train_LSTM.shape, Y_train_LSTM.shape, X_validation_LSTM.shape, Y_validation_LSTM.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From D:\\Anaconda\\lib\\site-packages\\tensorflow\\python\\framework\\op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Colocations handled automatically by placer.\n",
      "WARNING:tensorflow:From D:\\Anaconda\\lib\\site-packages\\tensorflow\\python\\ops\\math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use tf.cast instead.\n"
     ]
    }
   ],
   "source": [
    "# design network\n",
    "from matplotlib import pyplot\n",
    "\n",
    "def create_LSTMmodel(neurons=12, learn_rate = 0.01, momentum=0):\n",
    "        # create model\n",
    "    model = Sequential()\n",
    "    model.add(LSTM(50, input_shape=(X_train_LSTM.shape[1], X_train_LSTM.shape[2])))\n",
    "    #More number of cells can be added if needed \n",
    "    model.add(Dense(1))\n",
    "    optimizer = SGD(lr=learn_rate, momentum=momentum)\n",
    "    model.compile(loss='mse', optimizer='adam')\n",
    "    return model\n",
    "LSTMModel = create_LSTMmodel(12, learn_rate = 0.01, momentum=0)\n",
    "LSTMModel_fit = LSTMModel.fit(X_train_LSTM, Y_train_LSTM, validation_data=(X_validation_LSTM, Y_validation_LSTM),epochs=50, batch_size=72, verbose=0, shuffle=False)# plot history\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Visual plot to check if the error is reducing\n",
    "pyplot.plot(LSTMModel_fit.history['loss'], label='train')\n",
    "pyplot.plot(LSTMModel_fit.history['val_loss'], label='test')\n",
    "pyplot.legend()\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.000906767112032725"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "error_Training_LSTM = mean_squared_error(Y_train_LSTM, LSTMModel.predict(X_train_LSTM))\n",
    "predicted = LSTMModel.predict(X_validation_LSTM)\n",
    "error_Test_LSTM = mean_squared_error(Y_validation,predicted)\n",
    "error_Test_LSTM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Overall Comparison of all the algorithms ( including Time Series Algorithms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# compare algorithms\n",
    "results.append(error_Test_ARIMA)\n",
    "results.append(error_Test_LSTM)\n",
    "names.append(\"ARIMA\")\n",
    "names.append(\"LSTM\")\n",
    "fig = pyplot.figure()\n",
    "fig.suptitle('Algorithm Comparison-Post Time Series')\n",
    "ax = fig.add_subplot(111)\n",
    "pyplot.boxplot(results)\n",
    "ax.set_xticklabels(names)\n",
    "fig.set_size_inches(15,8)\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Grid Search uses Cross validation which isn't appropriate for the time series models such as LSTM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='5'></a>\n",
    "# 6. Model Tuning and Grid Search\n",
    "This section shown the Grid search for all the Machine Learning and time series models mentioned in the book."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='5.1'></a>\n",
    "### 6.1. Common Regression, Ensemble and DeepNNRegressor Grid Search\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best: -0.000419 using {'fit_intercept': True}\n",
      "-0.000419 (0.000159) with: {'fit_intercept': True}\n",
      "-0.000419 (0.000158) with: {'fit_intercept': False}\n"
     ]
    }
   ],
   "source": [
    "# 1. Grid search : LinearRegression\n",
    "'''\n",
    "fit_intercept : boolean, optional, default True\n",
    "    whether to calculate the intercept for this model. If set\n",
    "    to False, no intercept will be used in calculations\n",
    "    (e.g. data is expected to be already centered).\n",
    "'''\n",
    "param_grid = {'fit_intercept': [True, False]}\n",
    "model = LinearRegression()\n",
    "kfold = KFold(n_splits=num_folds, random_state=seed)\n",
    "grid = GridSearchCV(estimator=model, param_grid=param_grid, scoring=scoring, cv=kfold)\n",
    "grid_result = grid.fit(X_train, Y_train)\n",
    "print(\"Best: %f using %s\" % (grid_result.best_score_, grid_result.best_params_))\n",
    "means = grid_result.cv_results_['mean_test_score']\n",
    "stds = grid_result.cv_results_['std_test_score']\n",
    "params = grid_result.cv_results_['params']\n",
    "for mean, stdev, param in zip(means, stds, params):\n",
    "    print(\"%f (%f) with: %r\" % (mean, stdev, param))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best: -0.003024 using {'alpha': 0.01}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.01}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.1}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.3}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.7}\n",
      "-0.003024 (0.001482) with: {'alpha': 1}\n",
      "-0.003024 (0.001482) with: {'alpha': 1.5}\n",
      "-0.003024 (0.001482) with: {'alpha': 3}\n",
      "-0.003024 (0.001482) with: {'alpha': 5}\n"
     ]
    }
   ],
   "source": [
    "# 2. Grid search : Lasso\n",
    "'''\n",
    "alpha : float, optional\n",
    "    Constant that multiplies the L1 term. Defaults to 1.0.\n",
    "    ``alpha = 0`` is equivalent to an ordinary least square, solved\n",
    "    by the :class:`LinearRegression` object. For numerical\n",
    "    reasons, using ``alpha = 0`` with the ``Lasso`` object is not advised.\n",
    "    Given this, you should use the :class:`LinearRegression` object.\n",
    "''' \n",
    "param_grid = {'alpha': [0.01, 0.1, 0.3, 0.7, 1, 1.5, 3, 5]}\n",
    "model = Lasso()\n",
    "kfold = KFold(n_splits=num_folds, random_state=seed)\n",
    "grid = GridSearchCV(estimator=model, param_grid=param_grid, scoring=scoring, cv=kfold)\n",
    "grid_result = grid.fit(X_train, Y_train)\n",
    "print(\"Best: %f using %s\" % (grid_result.best_score_, grid_result.best_params_))\n",
    "means = grid_result.cv_results_['mean_test_score']\n",
    "stds = grid_result.cv_results_['std_test_score']\n",
    "params = grid_result.cv_results_['params']\n",
    "for mean, stdev, param in zip(means, stds, params):\n",
    "    print(\"%f (%f) with: %r\" % (mean, stdev, param))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best: -0.001091 using {'alpha': 0.01, 'l1_ratio': 0.01}\n",
      "-0.001091 (0.000493) with: {'alpha': 0.01, 'l1_ratio': 0.01}\n",
      "-0.001526 (0.000750) with: {'alpha': 0.01, 'l1_ratio': 0.1}\n",
      "-0.002986 (0.001506) with: {'alpha': 0.01, 'l1_ratio': 0.3}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.01, 'l1_ratio': 0.5}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.01, 'l1_ratio': 0.7}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.01, 'l1_ratio': 0.9}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.01, 'l1_ratio': 0.99}\n",
      "-0.002616 (0.001297) with: {'alpha': 0.1, 'l1_ratio': 0.01}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.1, 'l1_ratio': 0.1}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.1, 'l1_ratio': 0.3}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.1, 'l1_ratio': 0.5}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.1, 'l1_ratio': 0.7}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.1, 'l1_ratio': 0.9}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.1, 'l1_ratio': 0.99}\n",
      "-0.003022 (0.001483) with: {'alpha': 0.3, 'l1_ratio': 0.01}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.3, 'l1_ratio': 0.1}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.3, 'l1_ratio': 0.3}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.3, 'l1_ratio': 0.5}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.3, 'l1_ratio': 0.7}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.3, 'l1_ratio': 0.9}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.3, 'l1_ratio': 0.99}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.7, 'l1_ratio': 0.01}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.7, 'l1_ratio': 0.1}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.7, 'l1_ratio': 0.3}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.7, 'l1_ratio': 0.5}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.7, 'l1_ratio': 0.7}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.7, 'l1_ratio': 0.9}\n",
      "-0.003024 (0.001482) with: {'alpha': 0.7, 'l1_ratio': 0.99}\n",
      "-0.003024 (0.001482) with: {'alpha': 1, 'l1_ratio': 0.01}\n",
      "-0.003024 (0.001482) with: {'alpha': 1, 'l1_ratio': 0.1}\n",
      "-0.003024 (0.001482) with: {'alpha': 1, 'l1_ratio': 0.3}\n",
      "-0.003024 (0.001482) with: {'alpha': 1, 'l1_ratio': 0.5}\n",
      "-0.003024 (0.001482) with: {'alpha': 1, 'l1_ratio': 0.7}\n",
      "-0.003024 (0.001482) with: {'alpha': 1, 'l1_ratio': 0.9}\n",
      "-0.003024 (0.001482) with: {'alpha': 1, 'l1_ratio': 0.99}\n",
      "-0.003024 (0.001482) with: {'alpha': 1.5, 'l1_ratio': 0.01}\n",
      "-0.003024 (0.001482) with: {'alpha': 1.5, 'l1_ratio': 0.1}\n",
      "-0.003024 (0.001482) with: {'alpha': 1.5, 'l1_ratio': 0.3}\n",
      "-0.003024 (0.001482) with: {'alpha': 1.5, 'l1_ratio': 0.5}\n",
      "-0.003024 (0.001482) with: {'alpha': 1.5, 'l1_ratio': 0.7}\n",
      "-0.003024 (0.001482) with: {'alpha': 1.5, 'l1_ratio': 0.9}\n",
      "-0.003024 (0.001482) with: {'alpha': 1.5, 'l1_ratio': 0.99}\n",
      "-0.003024 (0.001482) with: {'alpha': 3, 'l1_ratio': 0.01}\n",
      "-0.003024 (0.001482) with: {'alpha': 3, 'l1_ratio': 0.1}\n",
      "-0.003024 (0.001482) with: {'alpha': 3, 'l1_ratio': 0.3}\n",
      "-0.003024 (0.001482) with: {'alpha': 3, 'l1_ratio': 0.5}\n",
      "-0.003024 (0.001482) with: {'alpha': 3, 'l1_ratio': 0.7}\n",
      "-0.003024 (0.001482) with: {'alpha': 3, 'l1_ratio': 0.9}\n",
      "-0.003024 (0.001482) with: {'alpha': 3, 'l1_ratio': 0.99}\n",
      "-0.003024 (0.001482) with: {'alpha': 5, 'l1_ratio': 0.01}\n",
      "-0.003024 (0.001482) with: {'alpha': 5, 'l1_ratio': 0.1}\n",
      "-0.003024 (0.001482) with: {'alpha': 5, 'l1_ratio': 0.3}\n",
      "-0.003024 (0.001482) with: {'alpha': 5, 'l1_ratio': 0.5}\n",
      "-0.003024 (0.001482) with: {'alpha': 5, 'l1_ratio': 0.7}\n",
      "-0.003024 (0.001482) with: {'alpha': 5, 'l1_ratio': 0.9}\n",
      "-0.003024 (0.001482) with: {'alpha': 5, 'l1_ratio': 0.99}\n"
     ]
    }
   ],
   "source": [
    "# 3. Grid Search : ElasticNet\n",
    "'''\n",
    "alpha : float, optional\n",
    "    Constant that multiplies the penalty terms. Defaults to 1.0.\n",
    "    See the notes for the exact mathematical meaning of this\n",
    "    parameter.``alpha = 0`` is equivalent to an ordinary least square,\n",
    "    solved by the :class:`LinearRegression` object. For numerical\n",
    "    reasons, using ``alpha = 0`` with the ``Lasso`` object is not advised.\n",
    "    Given this, you should use the :class:`LinearRegression` object.\n",
    "\n",
    "l1_ratio : float\n",
    "    The ElasticNet mixing parameter, with ``0 <= l1_ratio <= 1``. For\n",
    "    ``l1_ratio = 0`` the penalty is an L2 penalty. ``For l1_ratio = 1`` it\n",
    "    is an L1 penalty.  For ``0 < l1_ratio < 1``, the penalty is a\n",
    "    combination of L1 and L2.\n",
    "'''\n",
    "param_grid = {'alpha': [0.01, 0.1, 0.3, 0.7, 1, 1.5, 3, 5],\n",
    "              'l1_ratio': [0.01, 0.1, 0.3, 0.5, 0.7, 0.9, 0.99]}\n",
    "model = ElasticNet()\n",
    "kfold = KFold(n_splits=num_folds, random_state=seed)\n",
    "grid = GridSearchCV(estimator=model, param_grid=param_grid, scoring=scoring, cv=kfold)\n",
    "grid_result = grid.fit(X_train, Y_train)\n",
    "print(\"Best: %f using %s\" % (grid_result.best_score_, grid_result.best_params_))\n",
    "means = grid_result.cv_results_['mean_test_score']\n",
    "stds = grid_result.cv_results_['std_test_score']\n",
    "params = grid_result.cv_results_['params']\n",
    "for mean, stdev, param in zip(means, stds, params):\n",
    "    print(\"%f (%f) with: %r\" % (mean, stdev, param))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best: -0.000860 using {'n_neighbors': 17}\n",
      "-0.001571 (0.000373) with: {'n_neighbors': 1}\n",
      "-0.001040 (0.000358) with: {'n_neighbors': 3}\n",
      "-0.000934 (0.000363) with: {'n_neighbors': 5}\n",
      "-0.000886 (0.000349) with: {'n_neighbors': 7}\n",
      "-0.000877 (0.000358) with: {'n_neighbors': 9}\n",
      "-0.000871 (0.000353) with: {'n_neighbors': 11}\n",
      "-0.000865 (0.000361) with: {'n_neighbors': 13}\n",
      "-0.000864 (0.000358) with: {'n_neighbors': 15}\n",
      "-0.000860 (0.000361) with: {'n_neighbors': 17}\n",
      "-0.000865 (0.000365) with: {'n_neighbors': 19}\n",
      "-0.000864 (0.000372) with: {'n_neighbors': 21}\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# 4. Grid search : KNeighborsRegressor \n",
    "'''\n",
    "n_neighbors : int, optional (default = 5)\n",
    "    Number of neighbors to use by default for :meth:`kneighbors` queries.\n",
    "'''\n",
    "param_grid = {'n_neighbors': [1,3,5,7,9,11,13,15,17,19,21]}\n",
    "model = KNeighborsRegressor()\n",
    "kfold = KFold(n_splits=num_folds, random_state=seed)\n",
    "grid = GridSearchCV(estimator=model, param_grid=param_grid, scoring=scoring, cv=kfold)\n",
    "grid_result = grid.fit(X_train, Y_train)\n",
    "print(\"Best: %f using %s\" % (grid_result.best_score_, grid_result.best_params_))\n",
    "means = grid_result.cv_results_['mean_test_score']\n",
    "stds = grid_result.cv_results_['std_test_score']\n",
    "params = grid_result.cv_results_['params']\n",
    "for mean, stdev, param in zip(means, stds, params):\n",
    "    print(\"%f (%f) with: %r\" % (mean, stdev, param))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best: -0.000780 using {'min_samples_split': 10}\n",
      "-0.000928 (0.000256) with: {'min_samples_split': 2}\n",
      "-0.000932 (0.000322) with: {'min_samples_split': 3}\n",
      "-0.000919 (0.000266) with: {'min_samples_split': 4}\n",
      "-0.000907 (0.000300) with: {'min_samples_split': 5}\n",
      "-0.000878 (0.000240) with: {'min_samples_split': 6}\n",
      "-0.000866 (0.000266) with: {'min_samples_split': 7}\n",
      "-0.000872 (0.000249) with: {'min_samples_split': 8}\n",
      "-0.000826 (0.000210) with: {'min_samples_split': 9}\n",
      "-0.000780 (0.000196) with: {'min_samples_split': 10}\n"
     ]
    }
   ],
   "source": [
    "# 5. Grid search : DecisionTreeRegressor \n",
    "'''\n",
    "min_samples_split : int, float, optional (default=2)\n",
    "    The minimum number of samples required to split an internal node:\n",
    "\n",
    "    - If int, then consider `min_samples_split` as the minimum number.\n",
    "    - If float, then `min_samples_split` is a percentage and\n",
    "      `ceil(min_samples_split * n_samples)` are the minimum\n",
    "      number of samples for each split.\n",
    "'''\n",
    "param_grid={'min_samples_split': [2,3,4,5,6,7,8,9,10]}\n",
    "model = DecisionTreeRegressor()\n",
    "kfold = KFold(n_splits=num_folds, random_state=seed)\n",
    "grid = GridSearchCV(estimator=model, param_grid=param_grid, scoring=scoring, cv=kfold)\n",
    "grid_result = grid.fit(X_train, Y_train)\n",
    "print(\"Best: %f using %s\" % (grid_result.best_score_, grid_result.best_params_))\n",
    "means = grid_result.cv_results_['mean_test_score']\n",
    "stds = grid_result.cv_results_['std_test_score']\n",
    "params = grid_result.cv_results_['params']\n",
    "for mean, stdev, param in zip(means, stds, params):\n",
    "    print(\"%f (%f) with: %r\" % (mean, stdev, param))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best: -0.000968 using {'C': 100, 'gamma': 0.01}\n",
      "-0.002999 (0.001492) with: {'C': 0.01, 'gamma': 0.001}\n",
      "-0.002928 (0.001476) with: {'C': 0.01, 'gamma': 0.01}\n",
      "-0.002514 (0.001316) with: {'C': 0.01, 'gamma': 0.1}\n",
      "-0.001806 (0.000995) with: {'C': 0.01, 'gamma': 1}\n",
      "-0.002982 (0.001488) with: {'C': 0.03, 'gamma': 0.001}\n",
      "-0.002792 (0.001428) with: {'C': 0.03, 'gamma': 0.01}\n",
      "-0.002106 (0.001121) with: {'C': 0.03, 'gamma': 0.1}\n",
      "-0.001586 (0.000873) with: {'C': 0.03, 'gamma': 1}\n",
      "-0.002928 (0.001476) with: {'C': 0.1, 'gamma': 0.001}\n",
      "-0.002509 (0.001311) with: {'C': 0.1, 'gamma': 0.01}\n",
      "-0.001779 (0.000943) with: {'C': 0.1, 'gamma': 0.1}\n",
      "-0.001240 (0.000610) with: {'C': 0.1, 'gamma': 1}\n",
      "-0.002791 (0.001427) with: {'C': 0.3, 'gamma': 0.001}\n",
      "-0.002097 (0.001120) with: {'C': 0.3, 'gamma': 0.01}\n",
      "-0.001542 (0.000810) with: {'C': 0.3, 'gamma': 0.1}\n",
      "-0.001218 (0.000536) with: {'C': 0.3, 'gamma': 1}\n",
      "-0.002508 (0.001310) with: {'C': 1, 'gamma': 0.001}\n",
      "-0.001776 (0.000941) with: {'C': 1, 'gamma': 0.01}\n",
      "-0.001208 (0.000574) with: {'C': 1, 'gamma': 0.1}\n",
      "-0.001177 (0.000493) with: {'C': 1, 'gamma': 1}\n",
      "-0.002097 (0.001114) with: {'C': 3, 'gamma': 0.001}\n",
      "-0.001546 (0.000818) with: {'C': 3, 'gamma': 0.01}\n",
      "-0.001132 (0.000492) with: {'C': 3, 'gamma': 0.1}\n",
      "-0.001177 (0.000493) with: {'C': 3, 'gamma': 1}\n",
      "-0.001776 (0.000941) with: {'C': 10, 'gamma': 0.001}\n",
      "-0.001179 (0.000590) with: {'C': 10, 'gamma': 0.01}\n",
      "-0.001065 (0.000409) with: {'C': 10, 'gamma': 0.1}\n",
      "-0.001177 (0.000493) with: {'C': 10, 'gamma': 1}\n",
      "-0.001549 (0.000823) with: {'C': 30, 'gamma': 0.001}\n",
      "-0.001151 (0.000540) with: {'C': 30, 'gamma': 0.01}\n",
      "-0.001065 (0.000409) with: {'C': 30, 'gamma': 0.1}\n",
      "-0.001177 (0.000493) with: {'C': 30, 'gamma': 1}\n",
      "-0.001178 (0.000594) with: {'C': 100, 'gamma': 0.001}\n",
      "-0.000968 (0.000413) with: {'C': 100, 'gamma': 0.01}\n",
      "-0.001065 (0.000409) with: {'C': 100, 'gamma': 0.1}\n",
      "-0.001177 (0.000493) with: {'C': 100, 'gamma': 1}\n"
     ]
    }
   ],
   "source": [
    "# 6. Grid search : SVR \n",
    "'''\n",
    "C : float, optional (default=1.0)\n",
    "    Penalty parameter C of the error term.\n",
    "\n",
    "epsilon : float, optional (default=0.1)\n",
    "     Epsilon in the epsilon-SVR model. It specifies the epsilon-tube\n",
    "     within which no penalty is associated in the training loss function\n",
    "     with points predicted within a distance epsilon from the actual\n",
    "     value.\n",
    "gamma : float, optional (default='auto')\n",
    "    Kernel coefficient for 'rbf', 'poly' and 'sigmoid'.\n",
    "    If gamma is 'auto' then 1/n_features will be used instead.\n",
    "'''\n",
    "param_grid={'C': [0.01, 0.03,0.1,0.3,1,3,10,30,100],\n",
    "            'gamma': [0.001, 0.01, 0.1, 1]},\n",
    "            #'epslion': [0.01, 0.1, 1]}\n",
    "model = SVR()\n",
    "kfold = KFold(n_splits=num_folds, random_state=seed)\n",
    "grid = GridSearchCV(estimator=model, param_grid=param_grid, scoring=scoring, cv=kfold)\n",
    "grid_result = grid.fit(X_train, Y_train)\n",
    "print(\"Best: %f using %s\" % (grid_result.best_score_, grid_result.best_params_))\n",
    "means = grid_result.cv_results_['mean_test_score']\n",
    "stds = grid_result.cv_results_['std_test_score']\n",
    "params = grid_result.cv_results_['params']\n",
    "for mean, stdev, param in zip(means, stds, params):\n",
    "    print(\"%f (%f) with: %r\" % (mean, stdev, param))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best: -0.000801 using {'hidden_layer_sizes': (50,)}\n",
      "-0.001169 (0.000496) with: {'hidden_layer_sizes': (20,)}\n",
      "-0.000801 (0.000337) with: {'hidden_layer_sizes': (50,)}\n",
      "-0.000994 (0.000372) with: {'hidden_layer_sizes': (20, 20)}\n",
      "-0.000880 (0.000292) with: {'hidden_layer_sizes': (20, 30, 20)}\n"
     ]
    }
   ],
   "source": [
    "# 7. Grid search : MLPRegressor \n",
    "'''\n",
    "hidden_layer_sizes : tuple, length = n_layers - 2, default (100,)\n",
    "    The ith element represents the number of neurons in the ith\n",
    "    hidden layer.\n",
    "'''\n",
    "param_grid={'hidden_layer_sizes': [(20,), (50,), (20,20), (20, 30, 20)]}\n",
    "model = MLPRegressor()\n",
    "kfold = KFold(n_splits=num_folds, random_state=seed)\n",
    "grid = GridSearchCV(estimator=model, param_grid=param_grid, scoring=scoring, cv=kfold)\n",
    "grid_result = grid.fit(X_train, Y_train)\n",
    "print(\"Best: %f using %s\" % (grid_result.best_score_, grid_result.best_params_))\n",
    "means = grid_result.cv_results_['mean_test_score']\n",
    "stds = grid_result.cv_results_['std_test_score']\n",
    "params = grid_result.cv_results_['params']\n",
    "for mean, stdev, param in zip(means, stds, params):\n",
    "    print(\"%f (%f) with: %r\" % (mean, stdev, param))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best: -0.000470 using {'n_estimators': 400}\n",
      "-0.000479 (0.000189) with: {'n_estimators': 50}\n",
      "-0.000470 (0.000182) with: {'n_estimators': 100}\n",
      "-0.000471 (0.000183) with: {'n_estimators': 150}\n",
      "-0.000470 (0.000182) with: {'n_estimators': 200}\n",
      "-0.000471 (0.000183) with: {'n_estimators': 250}\n",
      "-0.000473 (0.000185) with: {'n_estimators': 300}\n",
      "-0.000471 (0.000180) with: {'n_estimators': 350}\n",
      "-0.000470 (0.000181) with: {'n_estimators': 400}\n"
     ]
    }
   ],
   "source": [
    "# 8. Grid search : RandomForestRegressor \n",
    "'''\n",
    "n_estimators : integer, optional (default=10)\n",
    "    The number of trees in the forest.\n",
    "'''\n",
    "param_grid = {'n_estimators': [50,100,150,200,250,300,350,400]}\n",
    "model = RandomForestRegressor()\n",
    "kfold = KFold(n_splits=num_folds, random_state=seed)\n",
    "grid = GridSearchCV(estimator=model, param_grid=param_grid, scoring=scoring, cv=kfold)\n",
    "grid_result = grid.fit(X_train, Y_train)\n",
    "print(\"Best: %f using %s\" % (grid_result.best_score_, grid_result.best_params_))\n",
    "means = grid_result.cv_results_['mean_test_score']\n",
    "stds = grid_result.cv_results_['std_test_score']\n",
    "params = grid_result.cv_results_['params']\n",
    "for mean, stdev, param in zip(means, stds, params):\n",
    "    print(\"%f (%f) with: %r\" % (mean, stdev, param))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best: -0.000446 using {'n_estimators': 50}\n",
      "-0.000446 (0.000174) with: {'n_estimators': 50}\n",
      "-0.000461 (0.000182) with: {'n_estimators': 100}\n",
      "-0.000474 (0.000186) with: {'n_estimators': 150}\n",
      "-0.000484 (0.000191) with: {'n_estimators': 200}\n",
      "-0.000492 (0.000193) with: {'n_estimators': 250}\n",
      "-0.000498 (0.000193) with: {'n_estimators': 300}\n",
      "-0.000505 (0.000196) with: {'n_estimators': 350}\n",
      "-0.000511 (0.000195) with: {'n_estimators': 400}\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# 9. Grid search : GradientBoostingRegressor \n",
    "'''\n",
    "n_estimators:\n",
    "\n",
    "    The number of boosting stages to perform. Gradient boosting\n",
    "    is fairly robust to over-fitting so a large number usually\n",
    "    results in better performance.\n",
    "''' \n",
    "param_grid = {'n_estimators': [50,100,150,200,250,300,350,400]}\n",
    "model = GradientBoostingRegressor(random_state=seed)\n",
    "kfold = KFold(n_splits=num_folds, random_state=seed)\n",
    "grid = GridSearchCV(estimator=model, param_grid=param_grid, scoring=scoring, cv=kfold)\n",
    "grid_result = grid.fit(X_train, Y_train)\n",
    "print(\"Best: %f using %s\" % (grid_result.best_score_, grid_result.best_params_))\n",
    "means = grid_result.cv_results_['mean_test_score']\n",
    "stds = grid_result.cv_results_['std_test_score']\n",
    "params = grid_result.cv_results_['params']\n",
    "for mean, stdev, param in zip(means, stds, params):\n",
    "    print(\"%f (%f) with: %r\" % (mean, stdev, param))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best: -0.000470 using {'n_estimators': 400}\n",
      "-0.000472 (0.000186) with: {'n_estimators': 50}\n",
      "-0.000473 (0.000186) with: {'n_estimators': 100}\n",
      "-0.000474 (0.000189) with: {'n_estimators': 150}\n",
      "-0.000472 (0.000189) with: {'n_estimators': 200}\n",
      "-0.000471 (0.000190) with: {'n_estimators': 250}\n",
      "-0.000471 (0.000190) with: {'n_estimators': 300}\n",
      "-0.000470 (0.000189) with: {'n_estimators': 350}\n",
      "-0.000470 (0.000188) with: {'n_estimators': 400}\n"
     ]
    }
   ],
   "source": [
    "# 10. Grid search : ExtraTreesRegressor \n",
    "'''\n",
    "n_estimators : integer, optional (default=10)\n",
    "    The number of trees in the forest.\n",
    "''' \n",
    "param_grid = {'n_estimators': [50,100,150,200,250,300,350,400]}\n",
    "model = ExtraTreesRegressor(random_state=seed)\n",
    "kfold = KFold(n_splits=num_folds, random_state=seed)\n",
    "grid = GridSearchCV(estimator=model, param_grid=param_grid, scoring=scoring, cv=kfold)\n",
    "grid_result = grid.fit(X_train, Y_train)\n",
    "print(\"Best: %f using %s\" % (grid_result.best_score_, grid_result.best_params_))\n",
    "means = grid_result.cv_results_['mean_test_score']\n",
    "stds = grid_result.cv_results_['std_test_score']\n",
    "params = grid_result.cv_results_['params']\n",
    "for mean, stdev, param in zip(means, stds, params):\n",
    "    print(\"%f (%f) with: %r\" % (mean, stdev, param))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best: -0.000574 using {'learning_rate': 1, 'n_estimators': 50}\n",
      "-0.000574 (0.000189) with: {'learning_rate': 1, 'n_estimators': 50}\n",
      "-0.000607 (0.000195) with: {'learning_rate': 1, 'n_estimators': 100}\n",
      "-0.000613 (0.000181) with: {'learning_rate': 1, 'n_estimators': 150}\n",
      "-0.000625 (0.000180) with: {'learning_rate': 1, 'n_estimators': 200}\n",
      "-0.000634 (0.000180) with: {'learning_rate': 1, 'n_estimators': 250}\n",
      "-0.000640 (0.000182) with: {'learning_rate': 1, 'n_estimators': 300}\n",
      "-0.000641 (0.000184) with: {'learning_rate': 1, 'n_estimators': 350}\n",
      "-0.000639 (0.000182) with: {'learning_rate': 1, 'n_estimators': 400}\n",
      "-0.000606 (0.000191) with: {'learning_rate': 2, 'n_estimators': 50}\n",
      "-0.000609 (0.000189) with: {'learning_rate': 2, 'n_estimators': 100}\n",
      "-0.000610 (0.000188) with: {'learning_rate': 2, 'n_estimators': 150}\n",
      "-0.000620 (0.000189) with: {'learning_rate': 2, 'n_estimators': 200}\n",
      "-0.000620 (0.000189) with: {'learning_rate': 2, 'n_estimators': 250}\n",
      "-0.000621 (0.000184) with: {'learning_rate': 2, 'n_estimators': 300}\n",
      "-0.000625 (0.000182) with: {'learning_rate': 2, 'n_estimators': 350}\n",
      "-0.000623 (0.000185) with: {'learning_rate': 2, 'n_estimators': 400}\n",
      "-0.000630 (0.000185) with: {'learning_rate': 3, 'n_estimators': 50}\n",
      "-0.000613 (0.000184) with: {'learning_rate': 3, 'n_estimators': 100}\n",
      "-0.000616 (0.000184) with: {'learning_rate': 3, 'n_estimators': 150}\n",
      "-0.000613 (0.000192) with: {'learning_rate': 3, 'n_estimators': 200}\n",
      "-0.000617 (0.000187) with: {'learning_rate': 3, 'n_estimators': 250}\n",
      "-0.000617 (0.000187) with: {'learning_rate': 3, 'n_estimators': 300}\n",
      "-0.000615 (0.000190) with: {'learning_rate': 3, 'n_estimators': 350}\n",
      "-0.000615 (0.000192) with: {'learning_rate': 3, 'n_estimators': 400}\n"
     ]
    }
   ],
   "source": [
    "# 11. Grid search : AdaBoostRegre\n",
    "'''\n",
    "n_estimators : integer, optional (default=50)\n",
    "    The maximum number of estimators at which boosting is terminated.\n",
    "    In case of perfect fit, the learning procedure is stopped early.\n",
    "\n",
    "learning_rate : float, optional (default=1.)\n",
    "    Learning rate shrinks the contribution of each regressor by\n",
    "    ``learning_rate``. There is a trade-off between ``learning_rate`` and\n",
    "    ``n_estimators``.\n",
    "''' \n",
    "param_grid = {'n_estimators': [50,100,150,200,250,300,350,400],\n",
    "             'learning_rate': [1, 2, 3]}\n",
    "model = AdaBoostRegressor(random_state=seed)\n",
    "kfold = KFold(n_splits=num_folds, random_state=seed)\n",
    "grid = GridSearchCV(estimator=model, param_grid=param_grid, scoring=scoring, cv=kfold)\n",
    "grid_result = grid.fit(X_train, Y_train)\n",
    "print(\"Best: %f using %s\" % (grid_result.best_score_, grid_result.best_params_))\n",
    "means = grid_result.cv_results_['mean_test_score']\n",
    "stds = grid_result.cv_results_['std_test_score']\n",
    "params = grid_result.cv_results_['params']\n",
    "for mean, stdev, param in zip(means, stds, params):\n",
    "    print(\"%f (%f) with: %r\" % (mean, stdev, param))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 12. Grid search : KerasNNRegressor \n",
    "'''\n",
    "nn_shape : tuple, length = n_layers - 2, default (100,)\n",
    "    The ith element represents the number of neurons in the ith\n",
    "    hidden layer.\n",
    "''' \n",
    "#Add Deep Learning Regressor\n",
    "if ( EnableDeepLearningRegreesorFlag == 1):\n",
    "    param_grid={'nn_shape': [(20,), (50,), (20,20), (20, 30, 20)]}\n",
    "    model = KerasNNRegressor()\n",
    "    kfold = KFold(n_splits=num_folds, random_state=seed)\n",
    "    grid = GridSearchCV(estimator=model, param_grid=param_grid, scoring=scoring, cv=kfold)\n",
    "    grid_result = grid.fit(X_train, Y_train)\n",
    "    print(\"Best: %f using %s\" % (grid_result.best_score_, grid_result.best_params_))\n",
    "    means = grid_result.cv_results_['mean_test_score']\n",
    "    stds = grid_result.cv_results_['std_test_score']\n",
    "    params = grid_result.cv_results_['params']\n",
    "    for mean, stdev, param in zip(means, stds, params):\n",
    "        print(\"%f (%f) with: %r\" % (mean, stdev, param))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='5.2'></a>\n",
    "### 6.2. Grid Search- Time Series Models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ARIMA(0, 0, 0) MSE=0.0008313\n",
      "ARIMA(0, 0, 1) MSE=0.0006774\n",
      "ARIMA(1, 0, 0) MSE=0.0004115\n",
      "ARIMA(1, 0, 1) MSE=0.0004115\n",
      "ARIMA(2, 0, 0) MSE=0.0004115\n",
      "ARIMA(2, 0, 1) MSE=0.0004089\n",
      "Best ARIMA(2, 0, 1) MSE=0.0004089\n"
     ]
    }
   ],
   "source": [
    "#Grid Search for ARIMA Model\n",
    "#Change p,d and q and check for the best result\n",
    "\n",
    "# evaluate an ARIMA model for a given order (p,d,q)\n",
    "#Assuming that the train and Test Data is already defined before\n",
    "def evaluate_arima_model(arima_order):\n",
    "    #predicted = list()     \n",
    "    modelARIMA=ARIMA(endog=Y_train,exog=X_train_ARIMA,order=arima_order)\n",
    "    model_fit = modelARIMA.fit()   \n",
    "    #error on the test set\n",
    "#     tr_len = len(X_train_ARIMA)\n",
    "#     to_len = len(X_train_ARIMA) + len(X_validation_ARIMA)\n",
    "#     predicted = model_fit.predict(start = tr_len -1 ,end = to_len -1, exog = X_validation_ARIMA)[1:]\n",
    "#     error = mean_squared_error(predicted, Y_validation)\n",
    "    # error on the training set \n",
    "    error = mean_squared_error(Y_train, model_fit.fittedvalues)\n",
    "    return error\n",
    " \n",
    "# evaluate combinations of p, d and q values for an ARIMA model\n",
    "def evaluate_models(p_values, d_values, q_values): \n",
    "    best_score, best_cfg = float(\"inf\"), None\n",
    "    for p in p_values:\n",
    "        for d in d_values:\n",
    "            for q in q_values:\n",
    "                order = (p,d,q)                \n",
    "                try:\n",
    "                    mse = evaluate_arima_model(order)                    \n",
    "                    if mse < best_score:\n",
    "                        best_score, best_cfg = mse, order\n",
    "                    print('ARIMA%s MSE=%.7f' % (order,mse))\n",
    "                except:\n",
    "                    continue\n",
    "    print('Best ARIMA%s MSE=%.7f' % (best_cfg, best_score))\n",
    "    \n",
    "# evaluate parameters\n",
    "p_values = [0, 1, 2]\n",
    "d_values = range(0, 2)\n",
    "q_values = range(0, 2)\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "evaluate_models(p_values, d_values, q_values)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LSTM(1, 0.001, 0.0) MSE=0.0009191\n",
      "LSTM(1, 0.001, 0.9) MSE=0.0009221\n",
      "LSTM(1, 0.3, 0.0) MSE=0.0009202\n",
      "LSTM(1, 0.3, 0.9) MSE=0.0009252\n",
      "LSTM(5, 0.001, 0.0) MSE=0.0009294\n",
      "LSTM(5, 0.001, 0.9) MSE=0.0009371\n",
      "LSTM(5, 0.3, 0.0) MSE=0.0008902\n",
      "LSTM(5, 0.3, 0.9) MSE=0.0009274\n",
      "Best LSTM(5, 0.3, 0.0) MSE=0.0008902\n"
     ]
    }
   ],
   "source": [
    "#Grid Search for LSTM Model\n",
    "\n",
    "# evaluate an LSTM model for a given order (p,d,q)\n",
    "def evaluate_LSTM_model(neurons=12, learn_rate = 0.01, momentum=0):\n",
    "    #predicted = list()     \n",
    "    LSTMModel = create_LSTMmodel(neurons, learn_rate, momentum)\n",
    "    LSTMModel_fit = LSTMModel.fit(X_train_LSTM, Y_train_LSTM,epochs=50, batch_size=72, verbose=0, shuffle=False)\n",
    "    predicted = LSTMModel.predict(X_validation_LSTM)\n",
    "    error = mean_squared_error(predicted, Y_validation)\n",
    "    return error\n",
    "\n",
    "# evaluate combinations of different variables of LSTM Model\n",
    "def evaluate_combinations_LSTM(neurons, learn_rate, momentum): \n",
    "    best_score, best_cfg = float(\"inf\"), None\n",
    "    for n in neurons:\n",
    "        for l in learn_rate:\n",
    "            for m in momentum:\n",
    "                combination = (n,l,m)                \n",
    "                try:\n",
    "                    mse = evaluate_LSTM_model(n,l,m)                    \n",
    "                    if mse < best_score:\n",
    "                        best_score, best_cfg = mse, combination\n",
    "                    print('LSTM%s MSE=%.7f' % (combination,mse))\n",
    "                except:\n",
    "                    continue\n",
    "    print('Best LSTM%s MSE=%.7f' % (best_cfg, best_score))\n",
    "    \n",
    "# evaluate parameters\n",
    "neurons = [1, 5]\n",
    "learn_rate = [0.001, 0.3]\n",
    "momentum = [0.0, 0.9]\n",
    "#Other Parameters can be modified as well\n",
    "batch_size = [10, 20, 40, 60, 80, 100]\n",
    "epochs = [10, 50, 100]\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "evaluate_combinations_LSTM(neurons,learn_rate,momentum)    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='6'></a>\n",
    "# 7. Finalise the Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us select one of the model to finalize the data. Looking at the results for the Random Forest Model. Looking at the results for the RandomForestRegressor model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='6.1'></a>\n",
    "## 7.1. Results on the Test Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',\n",
       "                      max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
       "                      max_samples=None, min_impurity_decrease=0.0,\n",
       "                      min_impurity_split=None, min_samples_leaf=1,\n",
       "                      min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
       "                      n_estimators=250, n_jobs=None, oob_score=False,\n",
       "                      random_state=None, verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# prepare model\n",
    "#scaler = StandardScaler().fit(X_train)\n",
    "#rescaledX = scaler.transform(X_train)\n",
    "model = RandomForestRegressor(n_estimators=250) # rbf is default kernel\n",
    "model.fit(X_train, Y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "_cell_guid": "f9725666-3c21-69d1-ddf6-45e47d982444"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0010988744547435773\n",
      "0.770991173511421\n"
     ]
    }
   ],
   "source": [
    "# estimate accuracy on validation set\n",
    "# transform the validation dataset\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.metrics import r2_score\n",
    "#rescaledValidationX = scaler.transform(X_validation)\n",
    "predictions = model.predict(X_validation)\n",
    "print(mean_squared_error(Y_validation, predictions))\n",
    "print(r2_score(Y_validation, predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.0167129 , -0.00438854, -0.01720166, -0.01160175,  0.02395749,\n",
       "        0.04436422,  0.06058143,  0.05072532,  0.03095209,  0.01356325,\n",
       "        0.0099564 , -0.00842381,  0.01126788,  0.02380102,  0.03248117,\n",
       "        0.03365514,  0.04211669,  0.03820695,  0.04439574,  0.0403192 ,\n",
       "        0.05855186,  0.0601968 ,  0.05554876,  0.05474416,  0.04013627,\n",
       "        0.03683666,  0.02488511,  0.03476343,  0.03237849,  0.03032998,\n",
       "        0.03901389,  0.03749494,  0.03193098,  0.03607884, -0.03805946,\n",
       "       -0.05936762, -0.03391639, -0.04593652, -0.01443007, -0.02085788,\n",
       "       -0.03487344, -0.03638463, -0.03563088, -0.05473057, -0.11883956,\n",
       "       -0.04365186, -0.05839629, -0.08177799, -0.10658929, -0.0723141 ,\n",
       "       -0.06093034, -0.03757991, -0.00596715,  0.04780189,  0.02360587,\n",
       "       -0.01332828, -0.00785864, -0.03248047, -0.02820984,  0.00942003,\n",
       "       -0.01978709, -0.0491296 , -0.01526217,  0.02559211, -0.01487458,\n",
       "        0.01762112,  0.06623189,  0.05028198,  0.03630367,  0.05250258,\n",
       "        0.02850159,  0.02790157, -0.02360305, -0.01868513,  0.00697606,\n",
       "       -0.00318529, -0.01077579, -0.02886531, -0.02580073, -0.03335841,\n",
       "       -0.02376638, -0.0748171 , -0.02263548, -0.04121525, -0.06405095,\n",
       "       -0.07891746, -0.08067931, -0.11992439, -0.08315298, -0.06357971,\n",
       "       -0.03311136,  0.00101853, -0.02848928, -0.05496003, -0.04974282,\n",
       "       -0.00102415,  0.03035821,  0.02785181,  0.02478636,  0.04806699,\n",
       "        0.04101064,  0.01829691,  0.05229777,  0.02267048,  0.01806651,\n",
       "        0.0481161 ,  0.03338871,  0.03011497,  0.0037035 ,  0.01198423,\n",
       "        0.03953344,  0.01174706,  0.03181125,  0.02311203, -0.00352524,\n",
       "        0.04403766,  0.04774884,  0.06654194,  0.0939478 ,  0.06582213,\n",
       "        0.06795722,  0.06044436,  0.0311404 ,  0.03947465,  0.06407764,\n",
       "        0.06366104,  0.08626386,  0.05829807,  0.09237167,  0.06248199,\n",
       "        0.0558632 ,  0.05059528,  0.05819086,  0.04331141,  0.04031494,\n",
       "        0.0513537 ,  0.06387019,  0.0623841 ,  0.06447874,  0.05932441,\n",
       "        0.06000217,  0.06130364,  0.06089483,  0.05959214,  0.05165794,\n",
       "        0.05256753,  0.04758325,  0.03122795,  0.04806537,  0.06412759,\n",
       "        0.0575488 ,  0.07847543,  0.09702115,  0.09410662,  0.09518771,\n",
       "        0.07163633,  0.06018362,  0.07542479,  0.0671117 ,  0.04368917,\n",
       "        0.04781752,  0.04979013,  0.05813182,  0.02939386,  0.03673248,\n",
       "        0.04364695,  0.06457493,  0.04641177,  0.03707081,  0.03067347,\n",
       "        0.02349352,  0.01301813, -0.01934682, -0.02268155, -0.02533962,\n",
       "       -0.03180231, -0.03166371, -0.04222748, -0.03458348, -0.01020102,\n",
       "        0.02253789,  0.04601804,  0.04959232,  0.04032586,  0.05536184,\n",
       "        0.05111265,  0.04350028,  0.03341034,  0.04390949,  0.06987675,\n",
       "        0.0644903 ,  0.07425782,  0.05582975,  0.05744612,  0.07294485,\n",
       "        0.0579009 ,  0.08598981,  0.10871372,  0.1015554 ,  0.07215359,\n",
       "        0.05582903,  0.03559519,  0.03959765,  0.03844638,  0.05848534,\n",
       "        0.0477716 ,  0.03641636,  0.0372103 ,  0.01364644,  0.01196397,\n",
       "        0.01210995,  0.01321671,  0.01675325,  0.04413029,  0.04326638,\n",
       "        0.04270718,  0.00684118,  0.01085247, -0.00255595, -0.02286433,\n",
       "       -0.0147629 , -0.00803585,  0.01157987, -0.00253967, -0.01876178,\n",
       "       -0.00701802, -0.01346794, -0.01603001,  0.00978598,  0.01435514,\n",
       "       -0.00074282,  0.00544204, -0.0142785 , -0.04998315, -0.05158218,\n",
       "       -0.03088809, -0.02809887,  0.01282912,  0.01988682,  0.03721984,\n",
       "        0.03890533,  0.03490906, -0.00384669, -0.00531803,  0.02578539,\n",
       "       -0.00358208,  0.03529414,  0.03129913,  0.0088258 , -0.00174584,\n",
       "        0.04051517,  0.0025114 ,  0.00020497,  0.03579171,  0.03472466,\n",
       "        0.0328713 ,  0.00938281,  0.00113179, -0.00632527, -0.0106241 ,\n",
       "       -0.01208661, -0.0109079 , -0.01034006, -0.01091301,  0.00576056,\n",
       "        0.02670394,  0.01198276,  0.00566075,  0.03272409,  0.02710886,\n",
       "        0.00203157, -0.01606232, -0.00986223, -0.01519102, -0.00571757,\n",
       "        0.00651934,  0.00859579,  0.04311555,  0.02940964,  0.05489656,\n",
       "        0.04774512,  0.03694486,  0.04302572,  0.05375753,  0.03606795,\n",
       "        0.04383782,  0.04516068,  0.04173705,  0.04564357,  0.08100234,\n",
       "        0.09733963,  0.079205  ,  0.10191097,  0.09349076,  0.07248063,\n",
       "        0.07601309,  0.06137686,  0.06087738,  0.04779072,  0.04437849,\n",
       "        0.04292305,  0.04440576,  0.04354415,  0.05775496,  0.0422338 ,\n",
       "        0.03701114,  0.04643909,  0.04832221,  0.02886001,  0.02418378,\n",
       "        0.03465933,  0.04660973,  0.04862381,  0.04718371,  0.04777968,\n",
       "        0.04225872,  0.02693193,  0.04210093,  0.08859046,  0.0577928 ,\n",
       "        0.05424162,  0.04425763,  0.04914569,  0.05827294,  0.07302622,\n",
       "        0.05615673,  0.05454844,  0.0636011 ,  0.07458665,  0.07352579,\n",
       "        0.06051135,  0.05680841,  0.04436114,  0.0276868 ,  0.04065472,\n",
       "        0.07529548,  0.07334085,  0.07420636,  0.12768835,  0.12557607,\n",
       "        0.15197126,  0.13704117,  0.14095683,  0.13725351,  0.12839587,\n",
       "        0.1271493 ,  0.13057559,  0.11702096,  0.11071868,  0.08927316,\n",
       "        0.07623848,  0.02815564,  0.045036  , -0.03619496, -0.02910809,\n",
       "       -0.01998923, -0.01754365, -0.07310221, -0.08735329, -0.12336669,\n",
       "       -0.12054098, -0.12389039, -0.10056516, -0.12019732, -0.1006773 ,\n",
       "       -0.12272242, -0.09908782, -0.10078916, -0.10281921, -0.11932   ,\n",
       "       -0.12394929, -0.07523005, -0.05682079, -0.01546912, -0.07255817,\n",
       "       -0.07298098, -0.07628215, -0.06934202,  0.02163013,  0.04409767,\n",
       "        0.02553263,  0.04722916,  0.17142788,  0.07575054,  0.18675236,\n",
       "        0.18821385,  0.18214007,  0.1821226 ,  0.18667874,  0.11411365,\n",
       "        0.16722662,  0.09534586,  0.10113332,  0.08780007,  0.10610973,\n",
       "        0.10871661,  0.10965673,  0.16483241,  0.08664926,  0.10180859,\n",
       "        0.10586637,  0.12560925,  0.09032735,  0.04148171,  0.03237559,\n",
       "        0.03337614,  0.03844717,  0.03321158,  0.09264446,  0.04440193,\n",
       "        0.07560031,  0.02262409,  0.03612574,  0.07382977,  0.03103831,\n",
       "        0.02792928,  0.06119375,  0.02706105,  0.00241605,  0.02394367,\n",
       "        0.02341902,  0.02406397,  0.01848726,  0.03604506,  0.04319433,\n",
       "        0.05985671,  0.04314911,  0.06628985,  0.03415608,  0.09323744,\n",
       "        0.09162318,  0.06616782,  0.08581251,  0.0680896 ,  0.07405359,\n",
       "        0.09212332,  0.0918069 ,  0.09039409,  0.11782611,  0.09661128,\n",
       "        0.10242397,  0.10471816,  0.07383994,  0.08950468,  0.08463576,\n",
       "        0.08625374,  0.04592718,  0.04495769,  0.07856623,  0.04030275,\n",
       "        0.04163912])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='6.2'></a>\n",
    "## 7.2. Variable Intuition/Feature Importance\n",
    "Let us look into the Feature Importance of the Random Forest model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.88063619 0.01111496 0.01045559 0.0105939  0.0119909  0.00888741\n",
      " 0.00891842 0.01207416 0.01051047 0.01155166 0.0117194  0.01154695]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "model = RandomForestRegressor()\n",
    "model.fit(X_train,Y_train)\n",
    "print(model.feature_importances_) #use inbuilt class feature_importances of tree based regressors\n",
    "#plot graph of feature importances for better visualization\n",
    "feat_importances = pd.Series(model.feature_importances_, index=X.columns)\n",
    "feat_importances.nlargest(10).plot(kind='barh')\n",
    "pyplot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='6.3'></a>\n",
    "## 7.3. Save Model for Later Use"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save Model Using Pickle\n",
    "from pickle import dump\n",
    "from pickle import load\n",
    "\n",
    "# save the model to disk\n",
    "filename = 'finalized_model.sav'\n",
    "dump(model, open(filename, 'wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0010980621870578236\n"
     ]
    }
   ],
   "source": [
    "# some time later...\n",
    "# load the model from disk\n",
    "loaded_model = load(open(filename, 'rb'))\n",
    "# estimate accuracy on validation set\n",
    "#rescaledValidationX = scaler.transform(X_validation) #in case the data is scaled.\n",
    "#predictions = model.predict(rescaledValidationX)\n",
    "predictions = model.predict(X_validation)\n",
    "result = mean_squared_error(Y_validation, predictions)\n",
    "print(result)"
   ]
  }
 ],
 "metadata": {
  "_change_revision": 206,
  "_is_fork": false,
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}