{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "_This notebook contains code and comments from Section 3.3 of the book [Ensemble Methods for Machine Learning](https://www.manning.com/books/ensemble-methods-for-machine-learning). Please see the book for additional details on this topic. This notebook and code are released under the [MIT license](https://github.com/gkunapuli/ensemble-methods-notebooks/blob/master/LICENSE)._\n",
    "\n",
    "---\n",
    "\n",
    "## 3.3 Combining predictions by meta-learning\n",
    "\n",
    "In this section, we will look at another approach to constructing heterogeneous ensembles: meta-learning. Instead of carefully designing a combination function to combine predictions, we will learn a combination function over the individual predictions. That is, the predictions of the base estimators are given as inputs to a second-level learning algorithm. Thus, rather than designing one ourselves, we will learn a second-level meta-classification function.\n",
    "\n",
    "### 3.3.1 Stacking\n",
    "Stacking is the most common meta-learning method and gets its name because it stacks a second classifier on top of its base estimators. The general stacking procedure has two steps:\n",
    "1.\tlevel 1: fit base estimators on the training data; this step is the same as before and aims to create a diverse, heterogeneous set of base classifiers.\n",
    "2.\tlevel 2: construct a new data set from the output of the base classifiers, which become meta-features; meta-features can either be the predictions or the probability of predictions. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Ignore FutureWarnings\n",
    "# Currently generated by sklearn.neighbors which uses scipy.mode\n",
    "from warnings import simplefilter\n",
    "simplefilter(action='ignore', category=FutureWarning)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.datasets import make_moons\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X, y = make_moons(600, noise=0.25, random_state=13)\n",
    "X, Xval, y, yval = train_test_split(X, y, test_size=0.25)        # Set aside 25% of data for validation\n",
    "Xtrn, Xtst, ytrn, ytst = train_test_split(X, y, test_size=0.25)  # Set aside a further 25% of data for hold-out test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Simple example: construct a simple heterogeneous ensemble from a 3-nearest neighbor classifier (3nn) and a Gaussian naïve Bayes classifier (gnb) on our 2d synthetic data set. After training the classifiers (3nn and gnb), we can create new features, called meta-features from the **classifier confidences** of these two classifiers.\n",
    "\n",
    "We can visualize the classifier confidences with the code below. Darker colors indicate greater confidence in classification. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.cm as cm\n",
    "import matplotlib.colors as col\n",
    "\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "\n",
    "cmap = cm.get_cmap('RdBu')\n",
    "colors = cmap(np.linspace(0, 0.5, num=2))\n",
    "\n",
    "# Init plotting\n",
    "xMin, xMax = Xtrn[:, 0].min() - 0.25, Xtrn[:, 0].max() + 0.25\n",
    "yMin, yMax = Xtrn[:, 1].min() - 0.25, Xtrn[:, 1].max() + 0.25\n",
    "xMesh, yMesh = np.meshgrid(np.arange(xMin, xMax, 0.05),\n",
    "                           np.arange(yMin, yMax, 0.05))\n",
    "\n",
    "fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(8, 4))\n",
    "\n",
    "# Train a KNN classifier and visualize classifier confidences\n",
    "knn = KNeighborsClassifier(n_neighbors=3)\n",
    "knn.fit(Xtrn, ytrn)\n",
    "\n",
    "zMesh = knn.predict_proba(np.c_[xMesh.ravel(), yMesh.ravel()])[:, 1]\n",
    "zMesh = zMesh.reshape(xMesh.shape)\n",
    "\n",
    "# Plot the classifier\n",
    "ax[0].contourf(xMesh, yMesh, zMesh, cmap=cmap, levels=20, alpha=0.4, antialiased=True)\n",
    "ax[0].contour(xMesh, yMesh, zMesh, [0.5], linewidths=3, colors='k')\n",
    "ax[0].scatter(Xtrn[ytrn == 0, 0], Xtrn[ytrn == 0, 1], marker='o',\n",
    "              edgecolors='k', alpha=0.4, s=80, facecolors='none')\n",
    "ax[0].scatter(Xtrn[ytrn == 1, 0], Xtrn[ytrn == 1, 1], marker='s',\n",
    "              edgecolors='k', alpha=0.4, s=80, facecolors='none')\n",
    "ax[0].set_title('Meta-feature 1, from 3nn', fontsize=12)\n",
    "ax[0].set_xlabel('$x_1$', fontsize=12)\n",
    "ax[0].set_ylabel('$x_2$', fontsize=12)\n",
    "\n",
    "# Train a Gaussian naive Bayes classifier and visualize classifier confidences\n",
    "gnb = GaussianNB()\n",
    "gnb.fit(Xtrn, ytrn)\n",
    "zMesh = gnb.predict_proba(np.c_[xMesh.ravel(), yMesh.ravel()])[:, 1]\n",
    "zMesh = zMesh.reshape(xMesh.shape)\n",
    "ax[1].contourf(xMesh, yMesh, zMesh, cmap=cmap, levels=20, alpha=0.4, antialiased=True)\n",
    "ax[1].contour(xMesh, yMesh, zMesh, [0.5], linewidths=3, colors='k')\n",
    "ax[1].scatter(Xtrn[ytrn == 0, 0], Xtrn[ytrn == 0, 1], marker='o',\n",
    "              edgecolors='k', alpha=0.4, s=80, facecolors='none')\n",
    "ax[1].scatter(Xtrn[ytrn == 1, 0], Xtrn[ytrn == 1, 1], marker='s',\n",
    "              edgecolors='k', alpha=0.4, s=80, facecolors='none')\n",
    "ax[1].set_title('Meta-feature 2, from gnb', fontsize=12)\n",
    "ax[1].set_xlabel('$x_1$', fontsize=12)\n",
    "ax[1].set_ylabel('$x_2$', fontsize=12);\n",
    "\n",
    "fig.tight_layout()\n",
    "# plt.savefig('./figures/CH03_F11_Kunapuli.png', format='png', dpi=300, bbox_inches='tight');\n",
    "# plt.savefig('./figures/CH03_F11_Kunapuli.pdf', format='pdf', dpi=300, bbox_inches='tight');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have already developed most of the framework we need to quickly implement linear stacking. We can train individual base estimators using fit (Listing 3.1) and obtain meta-features from predict_individual (Listing 3.2). We reproduce these here.\n",
    "\n",
    "**Listing 3.1**: Fitting different base estimators"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.gaussian_process import GaussianProcessClassifier\n",
    "from sklearn.gaussian_process.kernels import RBF\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "\n",
    "estimators = [('dt', DecisionTreeClassifier(max_depth=5)),\n",
    "              ('svm', SVC(gamma=1.0, C=1.0, probability=True)),\n",
    "              ('gp', GaussianProcessClassifier(RBF(1.0))),\n",
    "           \t  ('3nn', KNeighborsClassifier(n_neighbors=3)),\n",
    "              ('rf',RandomForestClassifier(max_depth=3, n_estimators=25)),\n",
    "              ('gnb', GaussianNB())]\n",
    "\n",
    "def fit(estimators, X, y):\n",
    "    for model, estimator in estimators:\n",
    "        estimator.fit(X, y)\n",
    "    return estimators"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Listing 3.2**: Individual predictions of base estimators"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "def predict_individual(X, estimators, proba=False):\n",
    "    n_estimators = len(estimators)\n",
    "    n_samples = X.shape[0] \n",
    "\n",
    "    y = np.zeros((n_samples, n_estimators))\n",
    "    for i, (model, estimator) in enumerate(estimators):\n",
    "        if proba:\n",
    "            y[:, i] = estimator.predict_proba(X)[:, 1]  \n",
    "        else:\n",
    "            y[:, i] = estimator.predict(X)              \n",
    "    return y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use these functions to train a stacking classifier and make predictions with it.\n",
    "\n",
    "**Listing 3.8**: Stacking with a second estimator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fit_stacking(level1_estimators, level2_estimator, X, y, use_probabilities=False):\n",
    "\n",
    "    fit(level1_estimators, X, y)\n",
    "    \n",
    "    X_meta = predict_individual(X, estimators=level1_estimators, proba=use_probabilities)\n",
    "    \n",
    "    level2_estimator.fit(X_meta, y)\n",
    "\n",
    "    final_model = {'level-1': level1_estimators, \n",
    "                   'level-2': level2_estimator, \n",
    "                   'use-proba': use_probabilities}\n",
    "    \n",
    "    return final_model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Listing 3.9**: Making predictions with a stacked model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict_stacking(X, stacked_model):\n",
    "    level1_estimators = stacked_model['level-1']\n",
    "    use_probabilities = stacked_model['use-proba']\n",
    "\n",
    "    X_meta = predict_individual(X, estimators=level1_estimators, proba=use_probabilities)\n",
    "\n",
    "    level2_estimator = stacked_model['level-2']\n",
    "    y = level2_estimator.predict(X_meta)\n",
    "    \n",
    "    return y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[``LogisticRegression``](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) is often used as the meta-estimator or the second-level estimator. We can train a stacked model with LR using these functions defined above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.06194690265486724"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "meta_estimator = LogisticRegression(C=1.0, solver='lbfgs')\n",
    "\n",
    "stacking_model = fit_stacking(estimators, meta_estimator, Xtrn, ytrn, use_probabilities=True)\n",
    "ypred = predict_stacking(Xtst, stacking_model)\n",
    "tst_err = 1 - accuracy_score(ytst, ypred)\n",
    "tst_err"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualize the decision boundaries of two stacked models, one where predictions are used as meta-features and the other where prediction probabilities are used as the meta-features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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93X0PgouaXm1mJ+SzHCVKDU7pGw30MbMjLFDZzP5uZlUJDnbNAi43s/Jm1p7gINj8fELQEN0TTqOCmR0dDlsENDGzjAJe+zTQw8wOCle0u4CP3f2X7YU3s05mtvXCdysIPvQ5+YxaleBKt8sIVpq7EqaRYcH5L6q7+xaCA2Dzm8YOcfccgvf3ITOrF86rsZmdFI6yCKhtZtXz5FwNrDWzlkDfHZzto8ANZrZ/OL/qZrb15+NVCf6eS4ByZjYASNyCsgjYzba9qvAMoEv4929FcBzWTs3fgmvXHGFm5QkK2EaK4X2WpFWU9fofZlbTzJoCVxD8kAGCz+paYJWZNSb/RvhSM2tiZrUIjsOblM84hVlC8Pnbo4DhLwB7m9n54ee/fPgZ3ncHa0aBy2LBuWSOD9+fjfz+w4Nd9Qmwxsyus+BcWelmdoCZHRYOz7uuZxAcI7QEyDKzkwmOJyySItS6qgTLtjL8e92aZxKLSPg7uPsSgka4a5j9QoLjg3Zq/mZ2qpntFX5ZX0VwUHOp1x41OKXM3acT/NJhKEGD8CPB/k3cfTPQPny8nGCf9LMFTCcbOI1gn/JcgmuTnB0OfpPgYMSFZrY0n9dOA24h+AbxG8EHuUsRF+Ew4GMzW0twgNkV7j47n/HGE2zG/pXglw8f5Rl+PvBLuPm0D8Gm6OJwHcF7+lE47WkE32Rw9+8I/hOYHW5WbQRcQ7C1aQ3BCrtDRdvdnyP4BjgxnN9M4ORw8KsEm21/IHgvNrLtZt6tJwpcZmafh/dvIfh7rCD41dZTuzD/auEyrQjnv4xg07HEUBHX6/8QHAw7A3iR4LgdCD5rhxD8Z/Qi+dedp4DXCA6e/YngINsdybee4Bc874frX+s8w9cQ/CffhWDr0EKCz3ZmOEpRa0Zhy5IJ3EOwBWIhwdagG3ZkOQpYtmyCX8ceRHAg8lLgMYKt15BnXQ+X9XKCrVArCGrQ1B2cbYG1juBHHRXDHB8R1KFEjwAdzWyFmW09p87FBM3gMmB/guM/d3b+LcLHawm+uA9397d2cPl2ma5FJSIiIrGjLTgiIiISO2pwREREJHbU4IiIiEjsqMERERGR2EmNC2bthDp16njz3XaLOoZIsVmxfDk///wzVWrWpW7delQovyvn7Cp5s775aqm7F3iSxbhQrZFUNHfePDZs2kKlipWoU7t21HF2SUG1JrYNTvPdduOjjz+NOoZIsZg5cyZHHxX8qjZr8yZGPPYkdevndw7A5HHoPg0LOgt3rKjWSCpq2qQx61Yt5ohj2nL/Pwdv/wVJrKBao11UIklu9erVdOjQng3r14MZVwx4IOmbGxGRqKnBEUlykyY/w88//QhApx796HzmaREnEhFJfmpwRJLcqlUrc+9f2veS6IKIiKQQNTgiqcTyXv9QRETyowZHREREYkcNjoiIiMSOGhwRERGJHTU4Iklu9arVUUcQEUk5anBEktiXX37Jww89AEC12vWpXLlKxIlERFKDGhyRJLVixQo6dGjPxg0bMEvjngcGk5amVVZEpChULUWSUE5ODud37crcX34GoMtFV3HEUcdFnEpEJHWowRFJQoMG3cZrr74MwIGtT6B///4RJxIRSS2RNzhmNsbMFpvZzAKGtzGzVWY2I7wNKO2MIqXp5Zde4p67bgegbuPmDB02AtMJ/naZao1I2ZIMVxMfCwwFxhcyzn/d/dTSiSMSnblz53L++V1xd8pnVmT4qHFUqVI16lhxMRbVGpEyI/ItOO7+LrA86hwiyeDpiZNYHV576pLr72KPvfaJNlCMqNaIlC2RNzhFdKSZfWlmL5vZ/gWNZGa9zGy6mU1fumRJaeYTKRYb1q/Pvd+1S+cIk5RZqjUiMZEKDc7nQHN3/zMwBPh3QSO6+yh3b+XurerUrVta+UQkHlRrRGIk6Rscd1/t7mvD+y8B5c2sTsSxRCRmVGtE4iXpGxwza2DhT0jM7HCCzMuiTSUicaNaIxIvkf+KysyeBtoAdcxsPnArUB7A3R8FOgJ9zSwL2AB0cXePKK6IpCjVGpGyJfIGx93P2c7woQQ/7RQR2WmqNSJlS9LvohIRERHZUWpwREREJHbU4IiIiEjsqMERERGR2FGDIyIiIrGjBkckiehXySIixUMNjkiSWLJkCePGjgGgUpVqhOecExGRnaAGRyQJZGVlce6557Dg1/kAdOx+mRocEZFdoAZHJAnccssA3nnrTQAOPrYdl192WcSJRERSmxockYhlZ2czfNhgABo234shg4dp642IyC5SgyMSsZycHDasXw/AcW1PpWKlShEnEhFJfWpwREREJHbU4IiIiEjsqMERERGR2FGDIyIiIrGjBkdERERiRw2OiIiIxI4aHBEREYkdNTgiIiISO2pwREREJHbU4IiIiEjsqMERSSLuHnUEEZFYUIMjErG0tDQqVa4MwDuvP8+6tWsjTiQikvoib3DMbIyZLTazmQUMNzMbbGY/mtlXZnZIaWcUKUnp6en0u/wqABbNm02/yy/VlpwSoFojUrZE3uAAY4F2hQw/GWgR3noBI0ohk0ipGjjwVk5oeyIAX77/Go8MHhxxolgai2qNSJkReYPj7u8CywsZ5QxgvAc+AmqYWcPSSSdSOtLT0xn/xBNkVqgAwHMTRmorTjFTrREpWyJvcIqgMTAv4fH88DmRWHn44UfYtHEjAC0PORozizhRmaNaIxIjqdDgFJmZ9TKz6WY2femSJVHHESmy55+fyv333gVA/aZ78M8HHoo4kRRGtUYk+aVCg/Mr0DThcZPwuT9w91Hu3srdW9WpW7dUwonsKnfn0ksuASCjYmWGjRxL5SpVIk5VJqnWiMRIKjQ4U4ELwl84tAZWuftvUYcSKS5ZWVks/G0BAH/vcD6779ki4kRllmqNSIyUizqAmT0NtAHqmNl84FagPIC7Pwq8BJwC/AisB3pEk1Sk5GVkVog6Qmyp1oiULZE3OO5+znaGO3BpKcURkZhSrREpW1JhF5WIiIjIDlGDIyIiIrGjBkdERERiRw2OiIiIxI4aHBEREYkdNTgiIiISO2pwRCI2adLE3PuZFSpGmEREJD7U4IhEaMaMGfTt0xuASlVrcO7ZnSNOJCISD2pwRCKyYsUKOnRoz6aNGzFL48Eho6hbv0HUsUREYkENjkhERo4azbw5vwDQ5eKrOPzIY6MNJCJlwk8//cTKlSsASEuLbxsQ3yUTSXJLliwGoHxGJv2v7h9xGhEpC9avX5+75Rig1TFtI05UctTgiETMzDCzqGOISMy5O7179+LbmV8D8PfOF9LpzFMjTlVy1OCIiIiUAYMHD2HS008BsNeBhzHg1kERJypZanBERERi7oP33+f6664BoEad+owYOYZy5cpFnKpkqcERERGJsYULF9K5cyeys7JISy/Hw8PHUKt2nahjlTg1OCIR2bhhQ9QRRKQM6HnRxSxetBCAC6+4hQP/fEjEiUqHGhyRCHzx+eeM+78xANSs1zjiNCKpJysri8ceH8O7770fdZSk9+F77wLQ6ugT6NPr4ojTlB41OCKlbNmyZXTo0J7NmzdhaekMuuPeqCOJpJwrrriCS3pfRLu/Hc9HH34YdZyUUK9R0zL1i001OCKl7MIePZg/by4A5/W+hsNaHx1xIpHUMmXKvxg9cgQAWVu20KlTRxYtWhRxquTl7lFHiIQaHJFStHr1al5+6QUADmx9AldecUXEiURSz4QnJwCQlp4OwKKFv9Gpc2e2bNkSZaykNOLRkaxbtxaAylWrRZymdKnBESlFWVlZufcPOax1mdpcLFJctjYyjXbbm+NOOhOAj97/L9dee22EqZLP9E8/5Zqrgy9RVWvWoWePCyNOVLrU4IiISGoy4+77/knj3VsCMGzIIzzzzOSIQyWHZcuW0bFjB7Zs3kxaejoPDR1N3Xr1o45VqtTgSLHZuHEjK1euZOXKlWzevDnqOCISQ4sWLeLzLz4DoFy5DCpUqMiI0eOoUDnY/XLfffdHGS9pTHn2ORb8Oh+Av51+Dge3ah1xotKnBkeKxaRJE6ldszr16tQKbnVr88a0aVHHEpEY2bJlC+d0OZsl4QHFJ57WEYDGTZux7yFHAbBm9erI8iWTk078G1XDY27eeuU5fpn9Y8SJSl9SNDhm1s7MvjezH83s+nyGdzezJWY2I7xdFEVOyd8XX3zBRRdeuM0BfuvXreOcc7rwyy+/RBdMJA/VmtR27bXX8t5/g3O6HHfSmfTqWbaOKdkRzZs35//GjQNg84Z1XNKrO+vXrYs4VemKvMExs3RgGHAysB9wjpntl8+ok9z9oPD2WKmGlAItX76cjh07sGnTRszS6NSjH6eeHRSdlSuW075DezZu3BhxShHVmlQ3efIkhg15BIBGu+/DXfc+uM1B+lvvL126hKVLl0aSMdmcfvoZ9P9H0McvmvcTl/W7pEz9ZDzyBgc4HPjR3We7+2ZgInBGxJkkjy1bttC1W3f2bdlym9uBB+zHvDm/AHBOr6u5/vobGXTbnbRrfz4AM7+cwd4t9mLfli1pfeSRfPPNNxEuhZRxqjVJ5tNPPuHoY47hoYcfzn1uxowZHHHEEX+oNT17dAegQuWqjBg9jooVK20zrSOO+gsAq1et5NxzzyE7O7u0FiOp3XHH7Rzf9m8AfPn+azwyeHDEiUpPMlxKtDEwL+HxfOCIfMbrYGbHAT8AV7n7vLwjmFkvoBdAs2bNSiBq2fWPf/yDyRPGFzj8T0e15eqrrs59PHDQHXz/3Ux+/vYLFv62IPf5M844nU8/nU7NmjVLNK9IPlRrksiCBQs488zTWbJ4MZ9+9AHNmzXluOP+wllnnsGv8//wlgfMuGLAgzRp2vwPg3p2v4CP3n+bL/77Cm+/+QY33XQz99xzdwkvRfJLT09nwoSnOKzVocyfN5cnH72fY1ofRqsjjoo6WolLhganKJ4Hnnb3TWbWGxgHHJ93JHcfBYwCOLRVq7KzHa6ETZo0keFDg66/ToOmNG2x/zbDq9eqx+23Dthmc3H5jAxGPz6eW2+7nfVrV7Nu9Up++PIj5v7yM+d37crU558nLS0ZNiCKbEO1ppRc2u9ylixenPu4Z48e7H/AAbnNzT4HH0WlKtuemO7Yv55E5zNPy3d6ZsaQwcPodOZJ/DbnR/75wL20bn04Z555VsktRIqoXbs2U6Y8y7HHHM3mzZvo3+9iJk99nfoNGkUdrUQlQ4PzK9A04XGT8Llc7r4s4eFjwH2lkKvMcnceGTyYjz+Zjrvz8gv/BqBC5WqMefJfNG5atG+sNWvVYfDDj+ROs0f3rnz90Zu89urLnHhSO+rWq0/VatW4feAA6tcvW+dnkEio1iSRb77+EoCa9RqxYvEC1q1byycffwTAwce2Y/ToMTt8IsyKlSoxfNQ4upx5Ips2rOPC7t2Z9PdnATjqyNZcduklZfbkmgcfcgjDhg/n4ot6snbVcvpe3J2JU54nIyMz6mglJhm+Qn8KtDCz3c0sA+gCTE0cwcwaJjw8HZhVivnKnAf/+U+u7X8VUyZN4NnJT7Fh/Xow4/5HHi1yc5OXmTF02KPUbRxsWn73rWlMmTSBsaNHcPrpp7Np06biXASR/KjWJKHd9z2IDt0uzX3coNmeDH5k6E43Is1224N+NwV96dq1a5gyaQJTJk2g/5X9GDZ8RLFkTlXduvegR8/gauJzfviaW276ww8JYyXyBsfds4DLgFcJislkd//GzG4zs9PD0S43s2/M7EvgcqB7NGnj77/vvsstNwYf+owKFalVrxF1GzXnwisHcNSxf92laVepUpURo5+g2d4HUKteI6rWqA3AF599yoBbb93l7CKFUa1JHu5OVsJpJa677gaOOaULex14GI8+/iSVKlfepemf06k9F1x2I3UaNqNWvUZkZFYA4NprruL777/fpWmnusGDB3PwoYcBMG3qRJ5+5tmIE5WcZNhFhbu/BLyU57kBCfdvAG4o7VxlzYIFC+jSpTPZ2dmklyvPY088y/5/OqhY57H7ni147vnXAdi8eRPtT23Lb3N+5JWXX+bee+4p1nmJ5KVakxyGDR/B/HlzAaheqy7p6ek88tBDxTqPK/r144p+/QCY/vEH9L6gA1lbtvDqq6+xzz77FOu8UklmZiZTpkxh//1asmH9er74+F3O6dQ+6lglIvItOJIcNm/eTIeOHXMP+ut51a3F3tzklZGRSd1GwS6rnJycEp2XiCSHjz/6iGuvuQoIfqBwff+rt/OKXbfX3i1z7+e4ak2TJk2oVq06AB7j2qsGRwC46qqr+OyT4AC/40/tTO+LekacSETiZsWKFXTsGGxJSUsvx0PDHqNO3XpRx5KYSopdVBKtJ54Yz+iRwcF3zVocwJ13l94PRzIrBvvaf/zf9zw9aTLNm+9GlSpV+NMB+Z1gVkRS2QsvvsSihb8BcMGlN/DnQw4rlflmZlYgLT2dnOxsnpowgcMOb42Z0XLvvahVq1apZJDSpy04ZdyMGTO4pE8fACpVrcGI0WNL9WeDl1/Sl/Ry5cnOyqLbeV1oc0xrWh10AAMG6KBjkbhJvGxLxwLOZ1MSKlaqRNvTugAw4/Pp/PXYI2lzTGv2brGXzq4eY2pwyrDly5fToUP73OtIPThkFA0aNi7VDPsdeBA9rrjlD8/fc9ftTJ36n1LNIiLxNej2O9mt5Z+3eW71qpV0aN+eVatWRZRKSpJ2UZVR2dnZdD3vvG2uI3X4kcdGkqVvr4vZY+/9WbFsMZs2bmTk/TezacM6enTrxocff8Lee+8dSS4RKV4fvv9e7v1y5cqX6rwzMjJ58ulneeG1N8nOzmLmZx/y8pTxzP7pf3Tv1o0pzz5bZs6uPmvWLFYsD85pmV4uvm1AfJdMCnXrrQOZ9vqrwB+vIxWFk9r8fl2U8uUzePCWS1mzZjVnnXUWH3/8MVWqVIkwnYjsjFWrVnHyKacw47NPAcjKygJg9/0Opk690j97ecVKleh05qkA5Jx1OnPm/MK309/lxRemcuddd3PLzTeVeqaStGzZMk4++WRmfjVjm+ezs7Nzryreuk27CJKVjrLRrso2XnzhBe67504A6jXZnaFDRiTV6cvP7dyeM7sGxwX97/tZXHTRRbkro4ikhpycHLp368b0jz8kKysrt7mpUr0Wwx99PPKak5aWxrDhI6ndoAkAdwwawOuvvRZppuKUnZ3Neeedy4zPp+e+/1tvW+tph26XceYpJ0actORoC04Zk5OTQ9++QfOQUSG4bkvlJNw6cuONN/PtzC/5YcaHPPuvybzc/UJOaRffFVEkbv4z9QVefCG4Esbu+x3MnvsfSlp6Or0uOJd69Rtu59Wlo1r1GgwbOY6unU4ha/Mm+vTtw08/zY46VrGYOPkZ3pwWnFR1rwMP+8PxR7XrN+GaSy+OIlqpUYNTxmzevJmFvy0A4NTO3dl9zxYRJ8pfeno69933IGeeGOy6+uXneBQdkbLil19+X2eHjXgsaa9c3aLlfpzcvivPT3w895jEOPjl559z7496bBzVa9SMME00iryLysz+Zmajzeyg8HGvEkslpSIzs2LUEQpVoUJy55OSoVoTP8m+LmckeS3cVRUqxnv5CrIjW3AuBPoCN5tZLeCgEkkkJWrt2rVRR9gp69alZm7ZKao1IrLLduQg4zXuvtLdrwFOBErnFJRSbHJycrj4ootyHzdo0jzCNNtXvWZNKlSuBsB999zN7NnaTVVGqNaIyC7bkQbnxa133P16YHzxx5GSdMedd+Ue9Lf/4X/h3M4dIk5UuIyMTHr1HwTAqpUraN/+LNavXx9xKikFqjUissu22+CY2SNmZu6+zWll3X1IycWS4vbhBx9w523B5Q/qNGzGsGEjU+KkVt3O68LfO/cA4NuZX9OnT2/9ZDymVGskGeTE+OraZU1R/odbA0w1s0oAZnaSmb1fsrGkuE157jncHUtLZ+jIsVStVj3qSEU24Nbb2POAVgBMfGoCQ4YOizhRwVasWMFr095Ukdw5qjUSiWo1fr/g5u233xFhEilO221w3P1m4GngnbDYXA1cX9LBpHhlhyfZysisQIt99o04zY4pV64cI0aOoXrtegBcf21/Pvzgg4hT/dGKFSs44ojDObVdW/qEFzCVolOtkah0v6ArdRsHxyTedccgXnn55YgTSXEoyi6qE4CLgXVAHeByd/9vSQcTSVS7Tl0eGT6GtPRyZG3ZQqdOHVm6dGnUsXLl5ORwfteu/DL7JwDGjnmMMY8/FnGq1KJaI1GpUqUqw0aOo3xmRdyd88/vqh81xEBRdlHdBNzi7m2AjsAkMzu+RFNJsVqzZg2vvhpcdyojs0LEaXbegQcdSvfLg2vFLF60kEmTnynS61avXl3ix+0MGnQbr7267be+fv0u441p05g7d27ubfwTT+QOT/bzEEVAtUYis2eLfbjk+ruA8EcNHdqnzI8aVq9eHXWEpFSUXVTHu/t74f2vgZMB7aRMEe5Oz549+fGH7wA48YxzIk60a7p37Zp7f926ddsdf+DAQdSpVYOePXuWWJPzyssvc89dtwNQt3FzHh75BGnp6WzZvJmT253IXnvslnu7tv9VAFStUZvOHc4okTypSrVGonbBuQk/avj6q6T/UYO707dvX+rUqsENN9wYdZyks8M/o3H334ATSiCLlID7H3iQfz/7LwD2Ofgorruu7BzS8Nxzz3LXHcHPzJ8cP5YH//nPYp/H7Nmz6dr1PNyd8pkVGTZyHMe2acv5lxT8Pqelp/PQsMeoWatOseeJE9UaicIfftQwZGjEiQo2ZOgwHh89EoAH77+HiROfjjhRctmpa1G5+4biDiLF75233+bWm28AoGa9RgwfMZr09PSIU+2axJ+2f/XlFwWO991339GzR49tnrvlxus5vFUrjvvLX4oly/r162nf/ixWr1oJwKU33M2eLfYB4PLLLqNx8z1Ztvi3P7xu9xb7c3CrI4olQ9yp1qSur2bMyL2fCqek2Grrjxo6nd6WVcsWc921/Tms1aEcedRRUUfbxkcffsj11/bf5rnevS5m//0P4IADDuCrL2fkPh/1ldujoottxtT8+fPp0uVssrOzSS+fwZARY6hRs9b2X5jkKlaqRIs/Hc7/vvqEyROf5q0334B8Vt61a9awIdx/fnbPK/nX+OFkb9nM309pR7UaNbYZt2HDxkyePJk99tijyDncnT59evPtzK8B+HvnCzn/nLO3GafDaSfv4NKJpIZly5bRoWMn/vfDrPxHcGfJ4sUA7LHfISl1WgoIftTw8LDH6XneWWRnZXHiiW2pVr34lqFGjVqMHzeOQ1u1KnCc226/g8dGPUp2Tna+w1evWkXWli2kpZej7+XXMOzhe9mwfj1HH9WaKlWqsnRJ8P63PPgoMjIyiy17KkmKBsfM2gGPAOnAY+5+T57hmQRnMz0UWAac7e6/lHbOVLFp0ybat2/PsqVLALj46oHse8Cfow1VjAYPfZROp7Vl7arluUW0IGed35drr72O6rXqMOr+m9m0aRNLFi3aZpwlixbRvv1ZfPDBh1SqVKlIGYYMGcrEpyYAsNeBhzHg1kE7tzBSqlRrdl12djbnnXcuH/z37e2OW6laTYYMH1XimUrCnw5uRffLb2LMQ4PYtHEjSzZuLLZpL1m0iLPOOpNPp39G/fr1/zB84sSnuWPQgCJNq3u/G7mwT1+Wrt7IpMcfZuOGDWzcEGz4rF6rHo8MGVFsuVNN5A2OmaUDw4C/AfOBT81sqrt/mzBaT2CFu+9lZl2Ae4Gz/zg1AbjiiiuY8fl0ANqedjYXX9hjO69ILfXqN+SxJ/7F0JGjyc7aUvB4jXfjhmuuBKD3RT1JS0vjyxmfbzPO8sUL+P6LD/h25tf07t2L8eOf2O7m3A/ef5/rwk3D1WvXY8TIMZQrF/mqJNuhWlM8xo1/gjenvQ7Abi3/TMPmLfIdLz29HJf06kmDho1LM16xuqR3b8qll+frr2cU2zTXrV7BVx++wcLfFnDuOV149bXXt6kf69ev55LwPFoVKlfj4GNOLHBaBxz4Z3pf1BOAa675B5vTMlk4NzhVRXq58lzetzd16tYrtuypxqI+QtzMjgQGuvtJ4eMbANz97oRxXg3H+dDMygELgbpeSPhDW7Xyjz7+tGTDJ6Hx48ZyUc8LAWi+94FMnPJ8md08WRRZWVmc16U9P34dfFaOOrYNVapUKfQ1n336McuWLiEtvRxjnvo3Bx50aGlETTmH7tPwM3cveBt8KVOtKR7XXncdDz94P2np5Xjn0++oVLly1JFSirtzZb8+vPd6cF3AfldezYMPPJA7fNOmTTRv1pTly5ZSPrMiE6a8nHtsn+SvoFqTDF87GwPzEh7PB/IegZk7jrtnmdkqoDawzZnezKwX0AugWbNmJZU3aX3x+edc0rcvAFWq12TE6LFqbrZj6wGFHU87gVXLFhdps/tWPS6/Wc1NalGtKUZpaWlqbnaCmXHP/Q/R+azvWfDz9wx5+J8c2foIOnbsBEBmZiZjx47jjNNPZcumDVzaqxvPTH2NqlWrRZw89aTOoe1F4O6j3L2Vu7eqU7du1HFKVU5ODp3P7szmzZswS+OBwaOp36BR1LFSQq3adRj+2JPssd8hNNp9n+3eGu/eko7d+9G3d6+oo0tEynKtkV1XsWIlRoweR4XKVQG4qOeFfPPNN7nD2518MjfcFByDs2TBHK67vuyc3qM4JcMWnF+BpgmPm4TP5TfO/HCzcXWCAwAlNHfuXOb8HJxa/IzzenFY66MjTpRaWu53IM8892LUMaRkqdZI0mjStDlX3PIg997Qm/Xr1tG+/Vlc0C04XvLoY45hwIBbeOvNaXz4wfv88NXHEadNTcnQ4HwKtDCz3QmKSxfg3DzjTAW6AR8SnML9zcL2iZdFiW9Hg/CicSKyDdUaSSqdzzqNn777mn+NHcLPP/3IoAHBpWjSy5Vj2rQ32WOPPfnwg/dBH8GdEvkuKnfPAi4DXgVmAZPd/Rszu83MTg9HexyobWY/oisMb1dZPamTSGFUayQZXXfd9Rzyl1O2eS47K4vOZ3di4cKFEaWKh2TYgoO7vwS8lOe5AQn3NwKdSjuXiMSLao0km7S0NEaPepxZc5eSk+O888qzPP7QQJYsWsQbi14DoGJ4rI7smKRocERERMqyfZsF16bbr3cvfvruK95++dncYR3P7xNVrJQW+S4qERERCZgZd97zAM33PhCAU8++kG5dz4k4VWrSFpyYyMjIyL3/9fT38e4X6FgcEZEUVKFCRSZOeZ73P/uGNq0PjjpOytIWnJho3Lgxx7X5KwDvTXue4Y8+GnEiERHZWRkZmfz1yEP0RXUXqMGJkQkTnqJ+g4YAjB1yF199MT3iRCIiItFQgxMj9evXZ/LkZwDIyc5i0MCbI04kIiISDTU4MfP6tDdy79dtpBP+iYhI2aQGJ0ZefeUV7rx9IAB1Gjbj/nvvizaQiIhIRNTgxMTmzZvp3r0b7k75zAoMGzWOqtWqRx1LREQkEmpwYuLXX39l2dIlAHTu0Y+99m4ZcSIREZHoqMGJoWo1akcdQUREJFJqcERERCR21OCIiIhI7KjBERERkdhRgyMiIiKxowZHREREYkcNjoiIiMSOGhwRERGJHTU4IiIiEjtqcERERCR21OCIiIhI7KjBERERkdhRgyMiIiKxE2mDY2a1zOx1M/tf+G/NAsbLNrMZ4W1qaecUkdSmWiNS9kS9Bed64A13bwG8ET7OzwZ3Pyi8nV568VLHunXroo4gksxUa0TKmKgbnDOAceH9ccCZ0UVJXVu2bKFP3765j+s3ahphGpGkpFojUsZE3eDUd/ffwvsLgfoFjFfBzKab2UdmdmZBEzOzXuF405cuWVLcWZPWNddcwycfvg/AX9q159QT/xpxIpGko1ojUsaUK+kZmNk0oEE+g25KfODubmZewGSau/uvZrYH8KaZfe3uP+Udyd1HAaMADm3VqqBpxcrzz09lxLAhADTeoyV33fsAZhZxKpHSp1ojIolKvMFx97YFDTOzRWbW0N1/M7OGwOICpvFr+O9sM3sbOBj4Q9EpiyZNmgRARoVKPDp6PBUqVIw4kUg0VGtEJFHUu6imAt3C+92A/+QdwcxqmllmeL8OcDTwbaklTHJZWdkA1Khdj0ZNdOyNSAFUa0TKmKgbnHuAv5nZ/4C24WPMrJWZPRaOsy8w3cy+BN4C7nF3FR0R2RGqNSJlTInvoiqMuy8DTsjn+enAReH9D4ADSzmaiMSIao1I2RP1FhwRERGRYqcGR0RERGJHDY6IiIjEjhocERERiR01OCIiIhI7anBEREQkdtTgiIiISOyowREREZHYUYMjIiIisaMGR0RERGJHDY6IiIjEjhocERERiR01OCIiIhI7anBEREQkdtTgiIiISOyowUlhq1ev5rPPpgOQXq58xGlERESShxqcFOXudO/enTk/zwagzUmnR5xIREQkeajBSVF33X0PL0z9NwD7tTqOq6+6OtpAIiIiSUQNTgpaunQpdwwaAEDtBk0YNnwkaWn6U4qIiGyl/xVT0IIFC8jOzgbgnIuupFr1GtEGEhERSTJqcFJcRkZm1BFERESSjhocERERiR01OCIiIhI7kTY4ZtbJzL4xsxwza1XIeO3M7Hsz+9HMri/NjCKS+lRrRMqeqLfgzATaA+8WNIKZpQPDgJOB/YBzzGy/0omXnLYeYCwiRaZaI1LGlIty5u4+C8DMChvtcOBHd58djjsROAP4tsQDJqGcnBwG3npr7uPqNWtHmEYkNajWiJQ9UW/BKYrGwLyEx/PD5/7AzHqZ2XQzm750yZJSCVfabr/9Dl5+6QUADji8Dae0/UvEiURiQ7VGJEZKfAuOmU0DGuQz6CZ3/09xzsvdRwGjAA5t1cqLc9rJ4I1p07jrjkEA1G3UnKE6wZ9ILtUaEUlU4g2Ou7fdxUn8CjRNeNwkfK7MeXTkSNyd8pkVGDpyLFWrVos6kkjSUK0RkUSp8PX/U6CFme1uZhlAF2BqxJkisWH9egAaNN2TvfZuGXEakdhRrRGJkah/Jn6Wmc0HjgReNLNXw+cbmdlLAO6eBVwGvArMAia7+zdRZRaR1KNaI1L2RP0rqueA5/J5fgFwSsLjl4CXSjFa0lmzZg3fzgp+zJGWnh5xGpHUolojUvakwi6qMs/d6dGjB/PnzgHg6DYnRpxIREQkuanBSQH33HsfU//9LAAtDzmaK6+4MtpAIiIiSU4NTpL77bffGDTgJgBq1WvE8BGjSdcuKhERkUKpwUlyP8+eTU5ODgDdL7uB6jVqRpxIREQk+anBSSEVKlWOOoKIiEhKUIMjIiIisaMGR0RERGJHDY6IiIjEjhocERERiR01OCIiIhI7anBEREQkdtTgiIiISOyowRERkSLZuHEj06a9DkC5jMyI04gUTg2OiIgUyWWXXcbML2cAcPwpHaINI7IdanBERGS7Hh05ivFjxwCwW8s/M2DAoIgTiRRODU6S+/bbb3Lvm+nPJSKlb8uWLdx84/UAVK1Rm0dHjaV8RkbEqUQKp/8xk9hXX33F1VdfBUDFqtU5sc1REScSkbJow4YNrF61EoBTO3enbv0G0QYSKQI1OElq5cqVdOjQno0bNmCWxgOPjKRKlapRxxKRMq5cufJRRxApEjU4Ser7//3EqtVrAOjc8wpaH/2XiBOJiIikDnP3qDOUCDNbAsyJOsd21AGWRh2iGMRlOSA+y5IMy9Hc3etGnKHEqdaUqrgsB8RnWZJhOfKtNbFtcFKBmU1391ZR59hVcVkOiM+yxGU5pHjE5fMQl+WA+CxLMi+HdlGJiIhI7KjBERERkdhRgxOtUVEHKCZxWQ6Iz7LEZTmkeMTl8xCX5YD4LEvSLoeOwREREZHY0RYcERERiR01OCIiIhI7anAiZmadzOwbM8sxs6T8qV1hzKydmX1vZj+a2fVR59lZZjbGzBab2cyos+wKM2tqZm+Z2bfh5+qKqDNJ9FK9zkA8ak1c6gykRq1RgxO9mUB74N2og+woM0sHhgEnA/sB55jZftGm2mljgXZRhygGWUB/d98PaA1cmsJ/Eyk+KVtnIFa1ZizxqDOQArVGDU7E3H2Wu38fdY6ddDjwo7vPdvfNwETgjIgz7RR3fxdYHnWOXeXuv7n75+H9NcAsoHG0qSRqKV5nICa1Ji51BlKj1qjBkV3RGJiX8Hg+SfYBL8vMbDfgYODjiKOI7CrVmiSWrLWmXNQBygIzmwY0yGfQTe7+n9LOI/FnZlWAKcCV7r466jxS8lRnJArJXGvU4JQCd28bdYYS8ivQNOFxk/A5iZCZlScoOBPc/dmo80jpiHGdAdWapJTstUa7qGRXfAq0MLPdzSwD6AJMjThTmWZmBjwOzHL3f0adR6SYqNYkmVSoNWpwImZmZ5nZfOBI4EUzezXqTEXl7lnAZcCrBAeYTXb3b6JNtXPM7GngQ2AfM5tvZj2jzrSTjgbOB443sxnh7ZSoQ0m0UrnOQHxqTYzqDKRArdGlGkRERCR2tAVHREREYkcNjoiIiMSOGhwRERGJHTU4IiIiEjtqcERERCR21OCIiIhI7KjBERERkdhRgyNJw8zeMrO/hffvMLMhUWcSkXhRnSk7dC0qSSa3AreZWT2CK9OeHnEeEYkf1ZkyQmcylqRiZu8AVYA27r7GzPYAbgKqu3vHaNOJSByozpQN2kUlScPMDgQaApvdfQ2Au89291S+XouIJBHVmbJDDY4kBTNrCEwAzgDWmlm7iCOJSMyozpQtanAkcmZWCXgW6O/us4DbCfaTi4gUC9WZskfH4EhSM7PawJ3A34DH3P3uiCOJSMyozsSTGhwRERGJHe2iEhERkdhRgyMiIiKxowZHREREYkcNjoiIiMSOGhwRERGJHTU4IiIiEjtqcERERCR21OCIiIhI7Pw/45bwY59zWAcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "feature_type = ['Predictions as meta-features', 'Probabilities as meta-features']\n",
    "figure_numbers = [13, 14]\n",
    "\n",
    "cmap = cm.get_cmap('Blues')\n",
    "colors = cmap(np.linspace(0, 0.5, num=2))\n",
    "xMin, xMax = Xtrn[:, 0].min() - 0.25, Xtrn[:, 0].max() + 0.25\n",
    "yMin, yMax = Xtrn[:, 1].min() - 0.25, Xtrn[:, 1].max() + 0.25\n",
    "xMesh, yMesh = np.meshgrid(np.arange(xMin, xMax, 0.05),\n",
    "                           np.arange(yMin, yMax, 0.05))\n",
    "\n",
    "for f, scatter in enumerate([True, False]):\n",
    "    fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(8, 4))\n",
    "    for i, p in enumerate([False, True]):\n",
    "        model = fit_stacking(estimators, meta_estimator, Xtrn, ytrn, use_probabilities=p)\n",
    "        zMesh = predict_stacking(np.c_[xMesh.ravel(), yMesh.ravel()], model)\n",
    "        zMesh = zMesh.reshape(xMesh.shape)\n",
    "\n",
    "        # Compute the test error\n",
    "        # ypred = predict_stacking(Xtst, model)\n",
    "        # tst_err = 1 - accuracy_score(ytst, ypred)\n",
    "\n",
    "        ax[i].contourf(xMesh, yMesh, zMesh, cmap='Blues', alpha=0.2)\n",
    "        if scatter:\n",
    "            ax[i].contour(xMesh, yMesh, zMesh, [0.5], colors='k', linewidths=2.5)\n",
    "            ax[i].scatter(Xtrn[ytrn == 0, 0], Xtrn[ytrn == 0, 1], marker='o', \n",
    "                          c=col.rgb2hex(colors[0]), edgecolors='k', s=80, alpha=0.5)\n",
    "            ax[i].scatter(Xtrn[ytrn == 1, 0], Xtrn[ytrn == 1, 1], marker='s', \n",
    "                          c=col.rgb2hex(colors[1]), edgecolors='k', s=80, alpha=0.5)\n",
    "        else:\n",
    "            ax[i].contour(xMesh, yMesh, zMesh, [0.5], colors='k', linewidths=2.5)\n",
    "\n",
    "        # ax[i].text((xMax + xMin)/2-2, yMax-0.25, 'test err = {0:4.2f}%'.format(tst_err*100))\n",
    "        ax[i].set_title('{0}\\n{1}'.format('Simple Stacking', feature_type[i]))\n",
    "        ax[i].set_xlabel('$x_1$')\n",
    "        ax[i].set_ylabel('$x_2$')\n",
    "        \n",
    "    fig.tight_layout()\n",
    "#     pngFile = './figures/CH03_F{0:02d}_Kunapuli.png'.format(figure_numbers[f])\n",
    "#     plt.savefig(pngFile, dpi=300, format='png', bbox_inches='tight');\n",
    "#     pdfFile = './figures/CH03_F{0:02d}_Kunapuli.pdf'.format(figure_numbers[f])\n",
    "#     plt.savefig(pdfFile, dpi=300, format='pdf', bbox_inches='tight');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "### 3.3.2\tStacking with cross validation\n",
    "\n",
    "Cross validation is a model validation and evaluation procedure that is commonly employed to simulate out-of-sample testing, tune model hyper-parameters and test the effectiveness of machine learning models. \n",
    "\n",
    "The prefix “k-fold” is used to describe the number of subsets we will be partitioning our data set into. For example, in 5-fold cross validation, data is (often randomly) partitioned into 5 non-overlapping subsets. This gives rise to 5 folds, or combinations of these subsets for training and validation.\n",
    "\n",
    "A key part of stacking with cross validation is to split the data set into training and validation sets for each fold. ``scikit-learn`` contains many utilities to perform precisely this, and the one we will use is called [``model_selection.StratifiedKFold``](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedKFold.html?highlight=stratified%20k%20fold#sklearn.model_selection.StratifiedKFold), which returns stratified folds (this means that the folds preserve class distributions in the data set when generating folds). \n",
    "\n",
    "The listing below demonstrates how to perform stacking with cross-validation.\n",
    "\n",
    "**Listing 3.10**: Stacking with cross validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import StratifiedKFold\n",
    "\n",
    "def fit_stacking_with_CV(level1_estimators, level2_estimator, X, y, n_folds=5, use_probabilities=False):\n",
    "    n_samples = X.shape[0]\n",
    "    n_estimators = len(level1_estimators)\n",
    "    X_meta = np.zeros((n_samples, n_estimators))\n",
    "\n",
    "    splitter = StratifiedKFold(n_splits=n_folds, shuffle=True)\n",
    "    for trn, val in splitter.split(X, y):\n",
    "        level1_estimators = fit(level1_estimators, X[trn, :], y[trn])\n",
    "        X_meta[val, :] = predict_individual(X[val, :],\n",
    "                                           estimators=level1_estimators,  \n",
    "                                           proba=use_probabilities)\n",
    "\n",
    "    level2_estimator.fit(X_meta, y) \n",
    "\n",
    "    level1_estimators = fit(level1_estimators, X, y)\n",
    "\n",
    "    final_model = {'level-1': level1_estimators, \n",
    "                   'level-2': level2_estimator, \n",
    "                   'use-proba': use_probabilities}\n",
    "\n",
    "    return final_model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As before, ``LogisticRegression`` is used as the (level 2) meta-estimator. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.053097345132743334"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stacking_model = fit_stacking_with_CV(estimators, meta_estimator,  Xtrn, ytrn, \n",
    "                                      n_folds=5, use_probabilities=True)\n",
    "ypred = predict_stacking(Xtst, stacking_model)\n",
    "tst_err = 1 - accuracy_score(ytst, ypred)\n",
    "tst_err = 1 - accuracy_score(ytst, ypred)\n",
    "tst_err"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, as be fore, we visualize the decision boundaries of two stacked models, one where predictions are used as meta-features and the other where prediction probabilities are used as the meta-features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "feature_type = ['Predictions as meta-features', 'Probabilities as meta-features']\n",
    "figure_numbers = [17, 99]\n",
    "\n",
    "xMin, xMax = Xtrn[:, 0].min() - 0.25, Xtrn[:, 0].max() + 0.25\n",
    "yMin, yMax = Xtrn[:, 1].min() - 0.25, Xtrn[:, 1].max() + 0.25\n",
    "xMesh, yMesh = np.meshgrid(np.arange(xMin, xMax, 0.05),\n",
    "                           np.arange(yMin, yMax, 0.05))\n",
    "\n",
    "for f, scatter in enumerate([True, False]):\n",
    "    fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(8, 4))\n",
    "    for i, p in enumerate([False, True]):\n",
    "        model = fit_stacking_with_CV(estimators, meta_estimator, Xtrn, ytrn, use_probabilities=p)\n",
    "        zMesh = predict_stacking(np.c_[xMesh.ravel(), yMesh.ravel()], model)\n",
    "        zMesh = zMesh.reshape(xMesh.shape)\n",
    "\n",
    "        # Compute the test error\n",
    "        # ypred = predict_stacking(Xtst, model)\n",
    "        # tst_err = 1 - accuracy_score(ytst, ypred)\n",
    "        \n",
    "        ax[i].contourf(xMesh, yMesh, zMesh, cmap='Blues', alpha=0.2)\n",
    "        if scatter:\n",
    "            ax[i].contour(xMesh, yMesh, zMesh, [0.5], colors='k', linewidths=2.5)\n",
    "            ax[i].scatter(Xtrn[ytrn == 0, 0], Xtrn[ytrn == 0, 1], marker='o', \n",
    "                          c=col.rgb2hex(colors[0]), edgecolors='k', s=80, alpha=0.5)\n",
    "            ax[i].scatter(Xtrn[ytrn == 1, 0], Xtrn[ytrn == 1, 1], marker='s', \n",
    "                          c=col.rgb2hex(colors[1]), edgecolors='k', s=80, alpha=0.5)\n",
    "        else:\n",
    "            ax[i].contour(xMesh, yMesh, zMesh, [0.5], colors='k', linewidths=2.5)\n",
    "\n",
    "        # ax[i].text((xMax + xMin)/2-2, yMax-0.25, 'test err = {0:4.2f}%'.format(tst_err*100))\n",
    "        ax[i].set_title('{0}\\n{1}'.format('Simple Stacking', feature_type[i]))\n",
    "        ax[i].set_xlabel('$x_1$')\n",
    "        ax[i].set_ylabel('$x_2$')\n",
    "        \n",
    "    fig.tight_layout()\n",
    "#     pngFile = './figures/CH03_F{0:02d}_Kunapuli.png'.format(figure_numbers[f])\n",
    "#     plt.savefig(pngFile, dpi=300, format='png', bbox_inches='tight');\n",
    "#     pdfFile = './figures/CH03_F{0:02d}_Kunapuli.pdf'.format(figure_numbers[f])\n",
    "#     plt.savefig(pdfFile, dpi=300, format='pdf', bbox_inches='tight');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}