Overfitting_Generate_data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Load Require Libraries\n",
    "\n",
    "<hr>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy import stats\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "from sklearn.preprocessing import SplineTransformer\n",
    "\n",
    "seed = 123"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>\n",
    "\n",
    "##### Generate data\n",
    "\n",
    "<hr>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "nsize = 10\n",
    "sd1 = 1.5 \n",
    "sd2 = 2.3 \n",
    "corr = 0.3 \n",
    "covv = corr * sd1 * sd2 \n",
    "\n",
    "dat = pd.DataFrame(stats.multivariate_normal.rvs(size = nsize,\n",
    "        mean = [2, 2], cov = [[sd1**2, covv], [covv, sd2**2]], random_state = seed),\n",
    "                   columns = ['x', 'y'])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = dat['x'].values\n",
    "y = dat['y'].values\n",
    "\n",
    "fig, ax = plt.subplots(1, 1, figsize = (12, 12))\n",
    "ax.scatter(x, y, color = 'black', s = 50)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "\n",
    "## split data into train and test\n",
    "\n",
    "<hr> \n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "xtrain, xtest, ytrain, ytest = train_test_split(x, y, test_size = 0.3, \n",
    "                                                random_state = seed)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>\n",
    "\n",
    "## implement Linear Regression \n",
    "\n",
    "<hr> <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Mse Train Linear Model: 11.9527, \n",
      " \n",
      "      Mse Test Linear Model: 8.8459\n",
      "      \n"
     ]
    }
   ],
   "source": [
    "xx = xtrain[:, np.newaxis]\n",
    "yy = ytrain[:, np.newaxis]\n",
    "xx2 = xtest[:, np.newaxis]\n",
    "yy2 = ytest[:, np.newaxis]\n",
    "reg_fit = LinearRegression(fit_intercept = True)\n",
    "Model1 = reg_fit.fit(xx, yy)\n",
    "slope1 =  Model1.coef_[0]\n",
    "Intercept1 = Model1.intercept_[0]\n",
    "\n",
    "yhat_train_model1 = xtrain * slope1 * Intercept1\n",
    "yhat_test_model1 = xtest * slope1 * Intercept1\n",
    "MseTrain1 = mean_squared_error(ytrain, yhat_train_model1)\n",
    "MseTest1 = mean_squared_error(ytest, yhat_test_model1)\n",
    "print(\"\"\"\n",
    "      Mse Train Linear Model: {:.4f}, \\n \n",
    "      Mse Test Linear Model: {:.4f}\n",
    "      \"\"\".format(MseTrain1, MseTest1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "\n",
    "## implement Polynomial Regression \n",
    "\n",
    "<hr>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "Poly1 = PolynomialFeatures(degree = 3)\n",
    "Poly2 = PolynomialFeatures(degree = 7)\n",
    "reg_fit2 = LinearRegression()\n",
    "reg_fit3 = LinearRegression()\n",
    "\n",
    "xtrain_trans1 = Poly1.fit_transform(xx)\n",
    "xtrain_trans2 = Poly2.fit_transform(xx)\n",
    "\n",
    "Model2 = reg_fit2.fit(xtrain_trans1, yy)\n",
    "Model3 = reg_fit3.fit(xtrain_trans2, yy)\n",
    "\n",
    "\n",
    "xtest_trans1 = Poly1.fit_transform(xx2)\n",
    "xtest_trans2 = Poly2.fit_transform(xx2)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Mse Train Polynomial Model with Degree 3: 4.0598, \n",
      " \n",
      "      Mse Test Polynomial Model with Degree 3: 8.4410\n",
      "      \n",
      "\n",
      "      Mse Train Polynomial Model With Degree 7: 0.0000, \n",
      " \n",
      "      Mse Test Polynomial Model With Degree 7 : 26.4303\n",
      "      \n"
     ]
    }
   ],
   "source": [
    "coef_model2 = Model2.coef_[0]\n",
    "coef_model3 = Model3.coef_[0]\n",
    "coef_model2[0] = Model2.intercept_[0]\n",
    "coef_model3[0] = Model3.intercept_[0]\n",
    "\n",
    "yhat_train_model2 = xtrain_trans1 @ coef_model2.T \n",
    "yhat_test_model2 = xtest_trans1 @ coef_model2 \n",
    "\n",
    "yhat_train_model3 = xtrain_trans2 @ coef_model3.T \n",
    "yhat_test_model3 = xtest_trans2 @ coef_model3 \n",
    "\n",
    "MseTrain2 = mean_squared_error(ytrain, yhat_train_model2)\n",
    "MseTest2 = mean_squared_error(ytest, yhat_test_model2)\n",
    "print(\"\"\"\n",
    "      Mse Train Polynomial Model with Degree 3: {:.4f}, \\n \n",
    "      Mse Test Polynomial Model with Degree 3: {:.4f}\n",
    "      \"\"\".format(MseTrain2, MseTest2))\n",
    "\n",
    "\n",
    "MseTrain3 = mean_squared_error(ytrain, yhat_train_model3)\n",
    "MseTest3 = mean_squared_error(ytest, yhat_test_model3)\n",
    "print(\"\"\"\n",
    "      Mse Train Polynomial Model With Degree 7: {:.4f}, \\n \n",
    "      Mse Test Polynomial Model With Degree 7 : {:.4f}\n",
    "      \"\"\".format(MseTrain3, MseTest3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "\n",
    "### Implement Bspline Model \n",
    "\n",
    "<hr>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "      Mse Train Bspline Model: 0.0000, \n",
      " \n",
      "      Mse Test Bspline Model : 25.4706\n",
      "      \n"
     ]
    }
   ],
   "source": [
    "spline = SplineTransformer(degree = 3, n_knots = 5)\n",
    "xtrain_spline = spline.fit_transform(xx)\n",
    "xtest_spline = spline.fit_transform(xx2)\n",
    "\n",
    "reg_fit4 = LinearRegression()\n",
    "Model4 = reg_fit4.fit(xtrain_spline, yy)\n",
    "\n",
    "yhat_train_model4 = Model4.predict(xtrain_spline)\n",
    "yhat_test_model4 = Model4.predict(xtest_spline)\n",
    "MseTrain4 = mean_squared_error(yhat_train_model4, yy)\n",
    "MseTest4 = mean_squared_error(yhat_test_model4, ytest)\n",
    "\n",
    "print(\"\"\"\n",
    "      Mse Train Bspline Model: {:.4f}, \\n \n",
    "      Mse Test Bspline Model : {:.4f}\n",
    "      \"\"\".format(MseTrain4, MseTest4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>\n",
    "\n",
    "### Visualize Models \n",
    "\n",
    "<hr>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "text1_ax1 = \"OLS Model: MSE = \" + str(round(MseTrain1, 4))\n",
    "text2_ax1 = \"PolyNomial Model With Degree 3: MSE = \" + str(round(MseTrain2, 4))\n",
    "text3_ax1 = \"PolyNomial Model With Degree 7: MSE = \" + str(round(MseTrain3, 4))\n",
    "text4_ax1 = \"Bspline Model With Degree 3 and  Number of Knots = 5: MSE = \" + str(round(MseTrain4, 4))\n",
    "\n",
    "text1_ax2 = \"OLS Model: MSE = \" + str(round(MseTest1, 4))\n",
    "text2_ax2 = \"PolyNomial Model With Degree 3: MSE = \" + str(round(MseTest2, 4))\n",
    "text3_ax2 = \"PolyNomial Model With Degree 7: MSE = \" + str(round(MseTest3, 4))\n",
    "text4_ax2 = \"Bspline Model With Degree 3 and  Number of Knots = 5: MSE = \" + str(round(MseTest4, 4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x900 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xmin = x.min()\n",
    "xmax = x.max()\n",
    "\n",
    "ymin = y.min()\n",
    "ymax = y.max()\n",
    "\n",
    "xtrainMin = xtrain.min()\n",
    "xtrainMax = xtrain.max()\n",
    "ytrainMin = ytrain.min()\n",
    "ytrainMax = ytrain.max()\n",
    "\n",
    "xtestMin = xtest.min()\n",
    "xtestMax = xtest.max()\n",
    "ytestMin = ytest.min()\n",
    "ytestMax = ytest.max()\n",
    "\n",
    "xspace1 = np.linspace(xmin, xmax, num = 100)\n",
    "xspace2 = Poly1.fit_transform(xspace1[:, np.newaxis])\n",
    "xspace3 = Poly2.fit_transform(xspace1[:, np.newaxis])\n",
    "xspace_spline = spline.fit_transform(xspace1[:, np.newaxis])\n",
    "\n",
    "yhat1 = slope1 * xspace1 + Intercept1\n",
    "yhat1 = yhat1.reshape((100, 1))\n",
    "yhat2 =  xspace2 @ coef_model2.T\n",
    "yhat3 =  xspace3 @ coef_model3.T\n",
    "yhat4 = Model4.predict(xspace_spline)\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 9))\n",
    "\n",
    "ax1.spines[\"left\"].set_position((\"axes\", 0))\n",
    "ax1.spines['left'].set_color('purple')\n",
    "ax1.spines['bottom'].set_position(('data', 0))\n",
    "\n",
    "ax1.spines['left'].set_color('purple')\n",
    "ax1.spines['bottom'].set_position(('axes', 0))\n",
    "ax1.spines['left'].set_linewidth(3)\n",
    "ax1.spines['bottom'].set_linewidth(3)\n",
    "ax1.spines['bottom'].set_color('purple')\n",
    "\n",
    "ax2.spines[\"left\"].set_position((\"axes\", 0))\n",
    "ax2.spines['left'].set_color('purple')\n",
    "ax2.spines['bottom'].set_position(('axes', 0))\n",
    "\n",
    "ax2.spines['left'].set_color('purple')\n",
    "ax2.spines['bottom'].set_position(('axes', 0))\n",
    "ax2.spines['left'].set_linewidth(3)\n",
    "ax2.spines['bottom'].set_linewidth(3)\n",
    "ax2.spines['bottom'].set_color('purple')\n",
    "\n",
    "\n",
    "for i in ['top', 'right']:\n",
    "    ax1.spines[i].set_visible(False)\n",
    "    ax2.spines[i].set_visible(False)\n",
    "\n",
    "\n",
    "\n",
    "ax1.set_xlabel('$x_{train}$', {\"color\": 'red', \"size\": 25})\n",
    "ax2.set_xlabel('$x_{test}$', {\"color\": 'red', \"size\": 25})\n",
    "\n",
    "ax1.set_ylabel('$y_{trian}$', {'color': 'red', \"size\": 25})\n",
    "ax2.set_ylabel('$y_{test}$', {'color': 'red', \"size\": 25})\n",
    "\n",
    "\n",
    "ax1.scatter(xx, yy, color = 'black')\n",
    "ax1.plot(xspace1, yhat1, c = 'blue', label = text1_ax1)\n",
    "ax1.plot(xspace1, yhat2, c = \"brown\", label = text2_ax1)\n",
    "ax1.plot(xspace1, yhat3, c = \"violet\", label = text3_ax1)\n",
    "ax1.plot(xspace1, yhat4, c = \"green\", label = text4_ax1)\n",
    "\n",
    "ax2.scatter(xx2, yy2, color = 'black')\n",
    "ax2.plot(xspace1, yhat1, c = \"blue\", label = text1_ax2)\n",
    "ax2.plot(xspace1, yhat2, c = \"brown\", label = text2_ax2)\n",
    "ax2.plot(xspace1, yhat3, c = \"violet\", label = text3_ax2)\n",
    "ax2.plot(xspace1, yhat4, c = \"green\", label = text4_ax2)\n",
    "\n",
    "\n",
    "ax1.set_xlim((xmin - 1, xmax + 3))\n",
    "ax1.set_ylim((ymin - 1, ymax + 1))\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "ax2.set_xlim((xmin - 1, xmax + 3))\n",
    "ax2.set_ylim((ymin - 1, ymax + 1))\n",
    "ax1.set_xticks([])\n",
    "ax1.set_yticks([])\n",
    "ax2.set_xticks([])\n",
    "ax2.set_yticks([])\n",
    "ax1.legend()\n",
    "ax2.legend()\n",
    "plt.show()\n"
   ]
  }
 ],
 "metadata": {
  "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": "3.11.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}