Exercise_03_2_solution.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rF2trPuyzm9C"
   },
   "source": [
    "# Exercise 3.2 - Solution\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "ipcsUFDUzm9C"
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "NopU99AT9G7s",
    "outputId": "f658cfbd-efde-4e92-a9f8-a22c43a04666"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2021-06-17 11:54:40--  https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv\n",
      "Resolving archive.ics.uci.edu (archive.ics.uci.edu)... 128.195.10.252\n",
      "Connecting to archive.ics.uci.edu (archive.ics.uci.edu)|128.195.10.252|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 264426 (258K) [application/x-httpd-php]\n",
      "Saving to: ‘winequality-white.csv.1’\n",
      "\n",
      "winequality-white.c 100%[===================>] 258.23K   496KB/s    in 0.5s    \n",
      "\n",
      "2021-06-17 11:54:42 (496 KB/s) - ‘winequality-white.csv.1’ saved [264426/264426]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# The code snippet below is responsible for downloading the dataset\n",
    "# - for example when running via Google Colab.\n",
    "#\n",
    "# You can also directly download the file using the link if you work\n",
    "# with a local setup (in that case, ignore the !wget)\n",
    "\n",
    "!wget https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "5ONqeI5Uzm9H",
    "outputId": "39dc42b1-bd2b-4439-81d0-59fca4b8ce80"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('data:', (4898, 12))\n",
      "First example:\n",
      "('Features:', array([5.9000e+00, 2.9000e-01, 1.6000e-01, 7.9000e+00, 4.4000e-02,\n",
      "       4.8000e+01, 1.9700e+02, 9.9512e-01, 3.2100e+00, 3.6000e-01,\n",
      "       9.4000e+00]))\n",
      "('Quality:', 5.0)\n"
     ]
    }
   ],
   "source": [
    "# load all examples from the file\n",
    "data = np.genfromtxt('winequality-white.csv',delimiter=\";\",skip_header=1)\n",
    "\n",
    "print(\"data:\", data.shape)\n",
    "\n",
    "# Prepare for proper training\n",
    "np.random.shuffle(data) # randomly sort examples\n",
    "\n",
    "# take the first 3000 examples for training\n",
    "# (remember array slicing from last week)\n",
    "X_train = data[:3000,:11] # all features except last column\n",
    "y_train = data[:3000,11]  # quality column\n",
    "\n",
    "# and the remaining examples for testing\n",
    "X_test = data[3000:,:11] # all features except last column\n",
    "y_test = data[3000:,11] # quality column\n",
    "\n",
    "print(\"First example:\")\n",
    "print(\"Features:\", X_train[0])\n",
    "print(\"Quality:\", y_train[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jiwnyNHpzm9L"
   },
   "source": [
    "# Solution\n",
    "\n",
    "* First we want to understand the data better. Plot (`plt.hist`) the distribution of each of the features for the training data as well as the 2D distribution (either `plt.scatter` or `plt.hist2d`) of each feature versus quality. Also calculate the correlation coefficient (`np.corrcoef`) for each feature with quality. Which feature by itself seems most predictive for the quality?\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "68s7HLT-zm9M",
    "outputId": "23963e85-84e5-467f-e6a7-5fd9041cf25b",
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Feature:', 'fixed acidity')\n",
      "('Correlation coefficient:', -0.12254069556587474)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Feature:', 'volatile acidity')\n",
      "('Correlation coefficient:', -0.18705678684985722)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Feature:', 'citric acid')\n",
      "('Correlation coefficient:', -0.023930246358986624)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Feature:', 'residual sugar')\n",
      "('Correlation coefficient:', -0.105170907139558)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Feature:', 'chlorides')\n",
      "('Correlation coefficient:', -0.20983280019541595)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Feature:', 'free sulfur dioxide')\n",
      "('Correlation coefficient:', 0.03174244252877395)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ohNHxQlpdSIAyZmw6YxmP/aLAwfEC2Yzx9OScK4VPW7eigyNPH+XgeIGVnTmemZzkZ79+uuS2y5Zmueq1L6JvQ/eM5VPH8lQbFz6/izseGZu+3d/bM2ef+bpycD+79hxg0p2MGVs3ruLqvvUN7aPZZo/r1DiWW34ssxKXu29c49Er/HzSwM/n8z48PJy4/cF9o+zYvZ/CxGSdFYo0RzZjDFx61nTAJDmWc9kMO7esb1goXTm4ny/e+/ic5ds2rT5mQr/UuOayGd54bjc37R2ds7yR47tQzGxv0tmTtOfwHbjVzPaa2fZGNz4wNKKwl7Y0MekMDI1M305yLBcmJmfsM1+79hyoaXk7KjWuhYlJdu05UHJ5I8e3FaU9pfNSdx81sxXAbWb2iLvfVbxB/ESwHWD16tU1NX5Q0zjSxoqP36THciOP+cky/7svt7wdlRuvcvfxWM+UVF/hx9fTx90PAV8DziuxzXXunnf3fFdXV03tr+zMNaROkWYoPn6THsuNPOYzZjUtb0flxqvcfTzWMyW1wDezDjN77tTvwEXAg43so7+3h1w208gmRRZENmP09/ZM305yLOeymRn7zNfWjatqWt6OSo1rLpth68ZVJZc3cnxbUZpTOicDX7PomXQx8CV3/2YjO5h6c0Vn6UijLfRZOsXH8kKdpTP1xuyxfJZOqXGdGsf8act1lk4z1XqWjohI6FrpLB0REWkRCnwRkUAo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJROqBb2YZM9tnZrek3ZeIiJS3eAH6eB/wMHBCmp1cObifXXsOMOnekPYyZmQXwW8nG9PeuhUdHHn6KKPjhcT7dOaymMGTRyaqbpsxo+O4Rfzqd5OJ2t68djk3XH4+g/tGGRga4eB4gZWdOfp7e+jb0F12v+JxzpixdeMqru5bn/g+AYn6nN3PpjOW8dgvCnP2qaeeqf5HxwtkzJh0p7vKfa91nERakXmDArJk42anAv8E/AVwhbtfUmn7fD7vw8PDNfdz5eB+vnjv4/UVGbB1Kzp44snfUph49kkil82wc8v6kmFWbpy3bVqdOPQH942yY/f+in0meTxz2QznrD6Ru3/wy5rqKdV/uTpqqVmkWcxsr7vnk2yb9pTOtcCfAUfT7GTXngNpNn/MevTQ4TnBV5iYZGBopOT25ca5lvEfGBqp2meS9goTkyXDvtr+pfovV0ctNYu0g9QC38wuAQ65+94q2203s2EzGx4bG6urr0ZN40jkYJlpp3LjXMv4l2u7ePl8H89K+5frv9L6JDWLtIM0X+FvBl5nZo8BXwZebmZfnL2Ru1/n7nl3z3d1ddXVUcZsXoXKTCs7cyWXlxvnWsa/XNvFy+f7eFbav1z/ldYnqVmkHaQW+O6+w91Pdfc1wGXA7e6+LY2+tm5clUazx7x1KzrIZTMzluWyGfp7e0puX26caxn//t6eqn0maS+XzbB57fKa6ynVf7k6aqlZpB0cE+fhX923nm2bVjf0lX7GjOMzjWtv3YoOumt8RdiZy7JsaTbRthkzTlhSOshK2bx2ObddcQE7t6ynuzOHAd2duYpvRM4e54xZTW/YAvRt6K7aZ6l+Nq9dPmefGy4/v+Z6ivuf2ocq9z1JzSLtINWzdGpV71k6IiKhaqWzdEREpEUo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJhAJfRCQQi9Nq2MyOB+4ClsT93OjuV6XV32xv/od7uPsHv5y+vXntcm64/Px5tTm4b5SBoRFGxwtkzJh0p7szR39vD30buutq6+B4gZV1tlGpzc6lWdzhqcJEovbTqEdkIbTzsbvQtZu7p9OwmQEd7v4bM8sC/wa8z93vLbdPPp/34eHhefc9O+ynzCf0B/eNsmP3fgoTk3PW5bIZdm5Zn/iBKtVWrW3UUl+19tOoR2QhtPOx26jazWyvu+eTbJvalI5HfhPfzMY/6Ty7zFIq7CstT2JgaKRsmBYmJhkYGplXW7W2UUt91dpPox6RhdDOx24zak91Dt/MMmZ2P3AIuM3d95TYZruZDZvZ8NjYWJrlzMvB8cK81ifZtpY26tm31n7nU4/IQmjnY7cZtaca+O4+6e5nA6cC55nZmSW2uc7d8+6e7+rqSrOceVnZmZvX+iTb1tJGPfvW2u986hFZCO187Daj9gU5S8fdx4E7gFcvRH+b1y6vaXkS/b095LKZkuty2Qz9vT3zaqvWNmqpr1r7adQjshDa+dhtRu2pBb6ZdZlZZ/x7DngV8Eha/RW74fLz54T7fM/S6dvQzc4t6+mOn30zZgB0d+ZqfpOluC2rs41qbS5bmqUzl03Ufhr1iCyEdj52m1F7mmfpvBj4JyBD9MTyVXf/X5X2adRZOiIioajlLJ3UzsN39weADWm1LyIitdEnbUVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEApHaaZn1MLMx4McJNz8J+HmK5TSK6mws1dlYqrOxmlHnae6e6DIFLRX4tTCz4aTnnjaT6mws1dlYqrOxWr1OTemIiARCgS8iEoh2Dvzrml1AQqqzsVRnY6nOxmrpOtt2Dl9ERGrTzq/wRUSkBm0X+Gb2ajMbMbPvm9kHm13PFDNbZWZ3mNlDZvY9M3tfvHy5md1mZo/G/y5rdq0w/W1k+8zslvj26Wa2Jx7Xr5jZcS1QY6eZ3Whmj5jZw2Z2fiuOp5m9P37MHzSzXWZ2fKuMp5n9o5kdMrMHi5aVHEOL/G1c8wNmdk6T6xyIH/sHzOxrU5dbj9ftiOscMbPeZtZZtO4DZuZmdlJ8u2njWU5bBb6ZZYBPARcDLwS2mtkLm1vVtGeAD7j7C4FNwHvi2j4IfNvd1wHfjm+3gvcBDxfdvgb4G3f/r8CTwNubUtVMnwC+6e7PB84iqrelxtPMuoE/AfLufibR5cAvo3XG8/PM/eKhcmN4MbAu/tkOfHqBaoTSdd4GnOnuLwb+E9gBEP9dXQa8KN7n7+JsaFadmNkq4CLg8aLFzRzP0ty9bX6A84Ghots7gB3NrqtMrf9C9KUvI8Ap8bJTgJEWqO1Uoj/0lwO3AEb0YZHFpca5STWeCPyI+H2mouUtNZ5AN3AAWE50ufFbgN5WGk9gDfBgtTEE/h7YWmq7ZtQ5a90bgBvi32f83QNDwPnNrBO4kehFyWPASa0wnqV+2uoVPs/+cU15Il7WUsxsDdF3AewBTnb3n8Srfgqc3KSyil0L/BlwNL79PGDc3Z+Jb7fCuJ4OjAGfi6eerjezDlpsPN19FPgY0Su7nwBPAXtpvfEsVm4MW/nv623AN+LfW6pOM3s9MOru/zFrVUvVCW02pdMOzOw5wE3An7r7r4rXefQ039TToszsEuCQu+9tZh0JLAbOAT7t7huAw8yavmmR8VwGvJ7oCWol0MECfXdzI7TCGFZjZh8imjK9odm1zGZmS4E/Bz7c7FqSaLfAHwVWFd0+NV7WEswsSxT2N7j77njxz8zslHj9KcChZtUX2wy8zsweA75MNK3zCaDTzKa+Aa0VxvUJ4Al33xPfvpHoCaDVxvOVwI/cfczdJ4DdRGPcauNZrNwYttzfl5n9d+AS4M3xkxO0Vp1riZ7s/yP+mzoVuM/M/gutVSfQfoH/78C6+AyI44jeuLm5yTUB0TvywGeBh93940Wrbgb+OP79j4nm9pvG3Xe4+6nuvoZo/G539zcDdwCXxpu1Qp0/BQ6YWU+86BXAQ7TYeBJN5Wwys6XxMTBVZ0uN5yzlxvBm4C3x2SWbgKeKpn4WnJm9mmjq8XXufqRo1c3AZWa2xMxOJ3pT9LvNqNHd97v7CndfE/9NPQGcEx+/LTWeQHu9aRs/wb+G6B37HwAfanY9RXW9lOi/xg8A98c/ryGaH/828CjwLWB5s2stqvkC4Jb49zOI/mi+D/wzsKQF6jsbGI7HdBBY1orjCXwUeAR4EPgCsKRVxhPYRfTewgRRGL293BgSvXn/qfhvaz/RmUfNrPP7RHPgU39Pnyna/kNxnSPAxc2sc9b6x3j2TdumjWe5H33SVkQkEO02pSMiInVS4IuIBEKBLyISCAW+iEggFPgiIoFQ4MuCM7M/ia9+2dRPTprZBUVXC11iZt8ys/vN7E0Nav/zZnZp/Pv19V7oz8z+X7X2RZJYXH0TkYZ7N/BKd3+ieKGZLfZnrz+z0DYAuPvZSXeopV53f0e9hbn779W7r0gxvcKXBWVmnyH6UNI34uvIf8TMvmBmdwNfsOg6/QNm9u/xNcT/R9G+/UXLP1qi7Uz8qvdBM9tvZu+Pl99pZvn495Pij8AX77cC+CLwkvgV/loze6zouuZ5M7sz/n1GvbPaMTP7P/E12r8FrChaV1zD1ri+B83smnjZaRZdn/4kM1tkZv/XzC6K1/0mQfvnmtl3zGyvmQ1NXTpBpJhe4cuCcvd3xh+Zv9Ddf25mHyH6boOXunvBzLYTfQT9JWa2BLjbzG7l2euKn0f0Ccabzexl7n5XUfNnA90eXZceK/rCjCo1HTKzdwD/090vifettMt0vbOWvwHoidefTHSJhX8s3sDMVhJdK/9couvk32pmfe4+GIf/p4k+ofuQu9+apH2LruH0SeD17j4WT0n9BdEVJkWmKfClFdxcFJ4XAS8umps+kSjoL4p/9sXLnxMvLw78HwJnmNknga8DswMzjXqLvQzY5e6TwEEzu73ENi8B7nT3MYD4fYyXAYPufr2Z/SHwTqInr6Tt9wBnArfFT1QZoo//i8ygwJdWcLjodwPe6+5DxRtY9DV2O93978s14u5PmtlZRF9A8k7gj4he5T7Ds9OXxyesqdI+h0mBRZfaPTW++Rzg10l3Bb7n7uenUZccOzSHL61mCHhXPE2Bmf03i774ZAh4m0XfN4CZdcdz79PiOfdF7n4TcCXR5ZQhuqDVufHvSc9qKd7njQn3uQt4U/xewinAhSW2+S7wB/FcfQbYCnwnXncN0TXfPwz8Qw3tjwBdZnY+RJfpNrMXJaxZAqJX+NJqrif6Crn7LJqfGAP63P1WM3sBcE88bfEbYBszr4ffTfQNWVMvZHbE/34M+Gr8/sDXE9bxUeCzZva/gTsT7vM1ou8XeIjossn3zN7A3X9iZh8kunyyAV93938xsz8gmu7Z7O6TZvZGM3uru3+uWvvu/nQ8Bfa3ZnYi0d/1tcD3EtYtgdDVMkVEAqEpHRGRQCjwRUQCocAXEQmEAl9EJBAKfBGRQCjwRUQCocAXEQmEAl9EJBD/H7Mv3hGAH7shAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Feature:', 'total sulfur dioxide')\n",
      "('Correlation coefficient:', -0.1664347420545924)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Feature:', 'density')\n",
      "('Correlation coefficient:', -0.3011834986297155)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Feature:', 'pH')\n",
      "('Correlation coefficient:', 0.10582198539702228)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Feature:', 'sulphates')\n",
      "('Correlation coefficient:', 0.08806984058367662)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('Feature:', 'alcohol')\n",
      "('Correlation coefficient:', 0.430906610759339)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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g+wtgv7vrIw5FRJrIbLdHbgH6gHcDTxSbV1O4xcJ9ZrbJ3e9PtEIREamL2Y7wP0XhHvavdvfTAMW/tP2kmf0d8HYKd8UUEZEGN1vgXwF0T72fvbs/a2Z/BPwceEeSxYmISP3MdpXO2agPL3H3PDDi7oeSKUtEROpttsD/YdR9781sF/BwMiWJiEgSZjulcyNwwMzeS+EvawFyQBb4/SQLExGR+prtIw6HgS1m9lbgdcXmr7v7PYlXJiIidRX31grfAL6RcC0iIpKgWm+tICIiTUaBLyISCAW+iEggFPgiIoFQ4IuIBEKBLyISCAW+iEggFPgiIoFQ4IuIBCLuJ17VxMyeAE4DeeAld88luT0REZleooFfdJm7/zyplfcfHaZvYIiTo2Osacuye3sPvZs7a17fzf3H2H/4BHl3MmZct2Utj488x32PPT3ZZ9v6Vfzo1HM8dfrFegxBmszKpRmefSFf8nj1y5bx6Kkzk23dHa0lj+Patn4Vp06/ULGuLReeVzEvgYq2gw89WTIvV69Ywp4rXluxjwD0DQwxPDpGxoy8Oy9f3oI7/HJsfLLfZ+99tKKWGy/rrmmfi9pXJ+qo1/4bR6PUkQaLuN19/VZeOMLPxQ38XC7ng4ODsdfff3SYPQeOMTZ+bufLtmTYu2NDTS/Wzf3HuOPQ8aqXE2kmLRkDh/Gz9dn34+xzUftqyyIDg/H8uTrmsv/G0Sh11JOZHYl79iTpc/gO3G1mR8zshnqvvG9gqOSFAxgbz9M3MFTT+vYfPlGPskQa2nje6xb2EG+fi9pXx896ScjGXddcNEodaUn6lM6b3X3YzDqAg2b2iLt/e2qH4g+CGwC6urqqWvnJ0bGq2meTT/C3HZGFbLZ9rpp9stb9t97rTrKOtCR6hF+8nz7ufgr4KnBJRJ/b3D3n7rn29vaq1r+mLVtV+2wyZjUtJxK62fa5avbJWvffeq87yTrSkljgm1mrma2Y+D/wO8CD9dzG7u09ZFsyJW3ZlszkmzDVmngjTGQha8lY4bx1ncTZ56L21ZZFVng/ocp1zUWj1JGWJI/wVwPfNbMHgH8D/q+731XPDfRu7mTvjg10tmUxoLMtO6c3Wj7eu4FdW7smj/QzZuza2sW29atK+m1bv4rVK5bMtXxpUiuXZioed3e0lrSVP45r2/pVkeuKmpdRbeXzcvWKJezbualkH+m7ZiN9126ks3gEO7GOly9voS3bMtlv385NkbWUry/OPhe1r/Zdu5G+azbWbf+No1HqSEuiV+lUq9qrdEREQtdIV+mIiEiDUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIIBT4IiKBUOCLiARCgS8iEggFvohIIBIPfDPLmNlRM/ta0tsSEZHpLZ6HbXwIeBhYOQ/bmrP+o8P0DQxxcnSMNW1Zdm/voXdzZ0W/6//+e9z32NOTj7s7Wnn+xbMlywEV6/ry4PGS5batX8Wxn/6SZ1/IT7atXJrhqs2d7D98grw7GTOu27KWgw89yVOnX5zst3rFEi5/3Ssq+h3+8S949NSZktqeHRsvWRags2x8N/cfq1jX4yPPVdQLVLSdOv1CxTY7Viyt6HfkiWf4Vd4n25ZljL++ZmPF92nv139YMdaxF/MV36e/6t1Qsuy687Ic+vEzs34/brysu2KbUa/X4E+ejvX9jVrfZ+99dNbvSdx5E9UWNS+j5m/cZeOKu480qmavfy7M3WfvVevKzV4FfB64FbjJ3a+cqX8ul/PBwcHE6plN/9Fh9hw4xtj4uVDJtmTYu2NDyYQoD/soLRkDh/GzyX1/62FifIM/eZo7Dh1Pu5zUtCwyMBif8sMos8jIz/PrFzVvotqi5mXU/I0aV9SyccXdRxpVs9cfxcyOuHsuTt+kT+nsAz4MnE14O3XRNzBUMhEAxsbz9A0MlbTNFvZQ2MEaPezh3Pj2Hz6RdimpGj/rJaEIzHvYQ/S8iWqLmpdR8zdqXFHLxhV3H2lUzV7/XCUW+GZ2JXDK3Y/M0u8GMxs0s8GRkZGkyonl5OhYVe0LxcnRMfIJ/qYnySifl9XM01rndLPvI81e/1wleYS/DbjKzJ4Avgi81czuKO/k7re5e87dc+3t7QmWM7s1bdmq2heKNW1ZMmZplyFVKp+X1czTWud0s+8jzV7/XCUW+O6+x91f5e7rgHcB33D3XUltrx52b+8h25Ipacu2ZCbf+Jow8cblTFoyVjh/2uAmxnfdlrVpl5KqlkVWOFc+RSaF1y9q3kS1Rc3LqPkbNa6oZeOKu480qmavf650Hf4UvZs72btjA51tWYzCVSxRb+bc+f43VoR+d0dryXJ912yk79qNJW37dm6qWG7b+lWsXFo6AVcuzbBra9fkUXfGjF1bu1i9YklJv9UrlkT26+5oraitfFnKxvfx3g2R64qqN6otaptR/ZaVhc+yjLFv56aK71PUWKO+T+XLblu/Ktb3o3y5vms30ndN6ev1qWs3xv7+Ro0hzvckzryJaoual1HzN2pcc3mDMu4+0qiavf65SvQqnWqlfZWOiEizaaSrdEREpEEo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJhAJfRCQQi5NasZktA74NLC1u5yvufktS20tS/9Fh+gaGODk6xpq2LLu399C7uTPtsuasfFyXXdTOvY+MlIwTWJBjj3L5p7/Jo6fOTD7u7mjl4E2X1nUbceZSs823Zqs3ZObuyazYzIBWd3/OzFqA7wIfcvdD0y2Ty+V8cHAwkXpq1X90mD0HjjE2np9sy7Zk2LtjQ1NP6qhxlWtZZGAwnj83RxbC2KOUh/2EeoZ+nLnUbPOt2epdiMzsiLvn4vRN7JSOFzxXfNhS/JfMT5cE9Q0MVYTi2HievoGhlCqqj6hxlRs/6yVhDwtj7FGiwn6m9lrEmUvNNt+ard7QJXoO38wyZnY/cAo46O6HI/rcYGaDZjY4MjKSZDk1OTk6VlV7s5hL/c0+9rTEmUvNNt+ard7QJRr47p53903Aq4BLzOziiD63uXvO3XPt7e1JllOTNW3ZqtqbxVzqb/axpyXOXGq2+dZs9YZuXq7ScfdR4F7g7fOxvXravb2HbEumpC3bkpl8Q7NZRY2rXMsioyVjJW0LYexRujtaq2qvRZy51GzzrdnqDV1igW9m7WbWVvx/FrgceCSp7SWld3Mne3dsoLMtiwGdbdkF8YZU1Lh2be0qedx37Ub6rtm44MYe5eBNl1aEe72v0okzl5ptvjVbvaFL8iqd1wOfBzIUfrB8yd3/aqZlGvEqHRGRRlbNVTqJXYfv7j8ANie1fhERqY7+0lZEJBAKfBGRQCjwRUQCocAXEQmEAl9EJBCJXZZZCzMbAX5S4+LnAz+vYzlp0Bgag8bQGDSGeF7t7rFuU9BQgT8XZjYY91rURqUxNAaNoTFoDPWnUzoiIoFQ4IuIBGIhBf5taRdQBxpDY9AYGoPGUGcL5hy+iIjMbCEd4YuIyAwWROCb2Z+Z2UNm9qCZ7S9+gHpTMbMPFet/yMz+NO164jCz/2Vmp8zswSltq8zsoJk9Wvz68jRrnM00Y7i2+DqcNbOGucJiOtOMoc/MHjGzH5jZVyduVd6ophnDfy7Wf7+Z3W1ma9KscTZRY5jy3J+bmZvZ+WnUNqHpA9/MOoE/AXLufjGF2zG/K92qqlP8JLD3A5cAG4ErzezX060qltup/FCbvwDucfdu4J7i40Z2O5VjeBDYAXx73qupze1UjuEgcLG7vx74d2DPfBdVpdupHEOfu7+++Kl5XwM+Ou9VVed2Ij7kyczWAr8DHJ/vgso1feAXLQayZrYYWA6cTLmear0GOOzuz7v7S8C3KAROQ3P3bwNPlzVfTeFzECh+7Z3XoqoUNQZ3f9jdm+ZTuKcZw93FuQRwiMLHjDasacbw7JSHrUBDv+E4zf4A8LfAh2mA+ps+8N19GPgkhZ+ePwN+6e53p1tV1R4EfsvMzjOz5cAVwNqUa6rVanf/WfH/TwKr0yxGAHgv8C9pF1ELM7vVzE4A19P4R/gVzOxqYNjdH0i7FlgAgV88R3w1cAGwBmg1s13pVlUdd38Y+ARwN3AXcD+QT7WoOvDCJWCpH9WEzMw+ArwE3Jl2LbVw94+4+1oK9f+ntOupRvHg7S9poB9UTR/4wG8Dj7v7iLuPAweAN6VcU9Xc/XPu/hvu/hbgGQrnXZvRU2b2SoDi11Mp1xMsM/tD4Ergem/+66/vBP5D2kVUaT2FA9EHzOwJCqfVvm9mr0iroIUQ+MeBrWa23MwMeBvwcMo1Vc3MOopfuyicv/9CuhXV7P8Af1D8/x8A/zvFWoJlZm+ncN74Knd/Pu16amFm3VMeXg08klYttXD3Y+7e4e7r3H0d8FPgDe7+ZFo1LYg/vDKzjwE7KfzqehR4n7u/kG5V1TGz7wDnAePATe5+T8olzcrM9gOXUrgj4FPALUA/8CWgi8KdT9/p7lFvZDWEacbwNPAZoB0YBe539+1p1TibacawB1gK/KLY7ZC7fyCVAmOYZgxXAD3AWQpz6QPF9+waUtQY3P1zU55/gsLVhKndAXRBBL6IiMxuIZzSERGRGBT4IiKBUOCLiARCgS8iEggFvohIIBT4Eiwze6KWuxea2e1mdk0V/ddF3UFRZL4p8EVEAqHAlyCYWb+ZHSne5/6GiOffXbz3+gNm9o/FtnVm9o1i+z3Fv4Ke8BYz+1cz+/HE0b4V9BU/1+CYme2cp+GJxLI47QJE5sl73f1pM8sC/8/M/nniCTN7HXAz8CZ3/7mZrSo+9Rng8+7+eTN7L/DfOHe751cCbwYuonA7ia9QuCXGJgqfaXB+cTvNck99CYCO8CUUf2JmD1C4N/xaYOp9Wt4KfHniT96n3ArijZy7p9E/Ugj4Cf3uftbdf8i5W0C/Gdjv7nl3f4rC5xr8ZiKjEamBjvBlwTOzSyncVfWN7v68mX0TmOvHYE69V5PNcV0i80JH+BKClwHPFMP+ImBr2fPfAK41s/Og8Lm8xfZ/5dzHZV4PfGeW7XwH2GlmGTNrB94C/Fs9BiBSDzrClxDcBXzAzB4Ghiic1pnk7g+Z2a3At8wsT+GOq38IfBD4BzPbDYwA75llO1+lcBroAQof/PJhd3/SzNbVbygitdPdMkVEAqFTOiIigVDgi4gEQoEvIhIIBb6ISCAU+CIigVDgi4gEQoEvIhIIBb6ISCD+PzUXaVB7/xlWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "features = [\"fixed acidity\", \"volatile acidity\", \"citric acid\", \n",
    "            \"residual sugar\", \"chlorides\", \"free sulfur dioxide\", \n",
    "            \"total sulfur dioxide\", \"density\", \"pH\", \"sulphates\", \"alcohol\"]\n",
    "\n",
    "# Loop over all features\n",
    "for i_feat, feat in enumerate(features):\n",
    "    plt.clf()\n",
    "    print(\"Feature:\", feat)\n",
    "    print(\"Correlation coefficient:\", \n",
    "          np.corrcoef(X_train[:,i_feat],y_train)[0,1]) # Calulate correlation coefficient\n",
    "\n",
    "    # 1D Histogram \n",
    "    plt.hist(X_train[:,i_feat])\n",
    "    plt.xlabel(feat)\n",
    "    plt.ylabel(\"# Wines\")\n",
    "    plt.show()\n",
    "    \n",
    "    # Scatter Plot\n",
    "    plt.scatter(X_train[:,i_feat],y_train)\n",
    "    plt.xlabel(feat)\n",
    "    plt.ylabel(\"Quality\")\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UaeDWDuZ0Rnl"
   },
   "source": [
    "* Calculate the linear regression weights. Numpy provides functions for matrix multiplication (`np.matmul`), matrix transposition (`.T`) and matrix inversion (`np.linalg.inv`).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "P-G2ydeLzm9P",
    "outputId": "e55f88bd-0c76-4a69-f517-9a645a6e77d6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(11,)\n",
      "[-5.30812726e-02 -1.97442032e+00 -1.19023323e-01  2.29172964e-02\n",
      " -1.24241078e+00  6.22941888e-03 -1.13065895e-03  2.01271384e+00\n",
      "  1.73179624e-01  7.02324736e-01  3.58386901e-01]\n"
     ]
    }
   ],
   "source": [
    "# Calulate weights using train data\n",
    "# w = (X_T X)^{-1} X_T y\n",
    "w = np.matmul(np.matmul(np.linalg.inv(np.matmul(X_train.T, X_train)), X_train.T),y_train)\n",
    "print(w.shape)\n",
    "print(w)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "aQIx9onx0Q9k"
   },
   "source": [
    "* Use the weights to predict the quality for the test dataset. How\n",
    "does your predicted quality compare with the true quality of the test data? Calculate the correlation coefficient between predicted and true quality and draw a scatter plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 419
    },
    "id": "v6LqA03Pzm9R",
    "outputId": "00f7e921-d676-4fcd-9fcf-d11960cf6e24"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "((1898, 11), (11,), (1898,))\n",
      "[6.7000e+00 3.0000e-01 2.9000e-01 2.8000e+00 2.5000e-02 3.7000e+01\n",
      " 1.0700e+02 9.9159e-01 3.3100e+00 6.3000e-01 1.1300e+01]\n",
      "[-5.30812726e-02 -1.97442032e+00 -1.19023323e-01  2.29172964e-02\n",
      " -1.24241078e+00  6.22941888e-03 -1.13065895e-03  2.01271384e+00\n",
      "  1.73179624e-01  7.02324736e-01  3.58386901e-01]\n",
      "6.221376799160009\n",
      "('Correlation coefficient:', 0.5089214775108005)\n"
     ]
    },
    {
     "data": {
      "image/png": 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sFoodHUNZnxr36S25LNufm+Xe7z3BGV/etlg6w8mnSks/t9qnf1EsUajsu5uHI256/fnLjq+4mh2/q+1rUJm7t2+12s7LZ/j5uIGfz+d9ZmYmtXrW4tDsPPsPHqVQLC1NizIGDsWaPTobZTiwZ0ddcE7e/iDFUvxxbtZv3fwh47qLt/LZI/N19axVNGRMXbsTgMnPPNhy/SKdFnefjjLG1DU7Ewd1s+O38VgdVGZ2JO7Vk7Sv4TvwJTM7Ymb7Ul5Xqqam55btiMWSLwvFQrHE1PRc3XJJwr5Vv3Xzzzi3HT7W0bCv9js1PVeuWWEvXRR3ny6WvO74iqvZ8dt4rIYg7Us6v+ru82Z2NnC3mT3q7l+pbVD5RbAPYNu2bSmXs3rHFwuraptkuSRKKf1llla9Iu3E3adXs4+2Wia0/T3VM3x3n6/8+zhwB3Bxkza3unve3fMjIyNplrMmW3LZVbVNslwSGbNU+t2Sy6ZWs8hK4u7Tq9k/Wy0T2r6eWuCb2SYze3b1e+BK4OG01pe2yfExslGmblqUMaKh+p00G2WW3nStLhdlkoVzs37r5g8Ze3dvXVbPWkVDxuT4WLnmFdYv0mlx9+koY3XHV1zNjt/GYzUEaV7SeT5wh5V/a28APunud6W4vlRV39hJepdO9fs07tLJv/Cs1O7SAXSXjsTWqbt0GvfpTt2l0+r4HfQ3bJNK9S6dpPr5Lh0RkX7UT3fpiIhIn1Dgi4gEQoEvIhIIBb6ISCAU+CIigVDgi4gEQoEvIhIIBb6ISCAU+CIigVDgi4gEQoEvIhIIBb6ISCAU+CIigVDgi4gEQoEvIhIIBb6ISCAU+CIigVDgi4gEQoEvIhIIBb6ISCAU+CIigVDgi4gEQoEvIhIIBb6ISCBSD3wzy5jZrJl9Pu11iYhIaxu6sI53At8EfiWtFRyanWdqeo7jiwW25LJMjo8xsWs0cZte1bbWvmqnPycbUSyd4eRTJQBy2Yirdr6Aex5dYH6xQMaMkju5bIQZLJ4qkhuOcIcThWLbGg/NzvPeOx9hsVBcmrZpY4YoM8SJQpEhg5I/3f68szfx9svPW7bMcDTExg0ZThSKPCcb8dTpEqeKZ5bmDxmccRhN+HpWp88vFjCgphSiITh9pn5atfba2mptHo74zZc/PX61fW7MGMWSL/08HA2x56Jz+MJDP+LJU8Vlbcwgu2GIQvFMy3F+00fu5evffWLp59r1mcGrXnwW3/9poe61HG2xLyR5XVuJs89183iKo59r6zVz9/atVtu52TnAx4A/Am5096tWap/P531mZibROg7NzrP/4FEKxdLStGyU4cCeHUsvcpw2aejkelv19caLRvnskfm66WvVqsZDs/NMfuZBimfS22fi1NPNsUhT43Y1hn3Svtptf9J9L8k4d+N4iqNXx3ovmdkRd8/HaZv2JZ1bgD8AzrRruFpT03PLdvBCscTU9FyiNr2qba193Xb4WMcDrlWNU9NzXQ/7ZvV0cyzS1Lhdqw37al/ttj/pvpdknLtxPMXRq2N9UKQW+GZ2FfC4ux9p026fmc2Y2czCwkLi9RxfLLSdHqdNGjq53lbLlFL6C63Z+tIer5XEeT3TGos0dXJM42x/kvUlHede7h/tauiH2vpBmmf4lwJXm9n3gb8CXmNmH29s5O63unve3fMjIyOJV7Ill207PU6bNHRyva2WyZgl7mu160t7vFYS5/VMayzS1MkxjbP9SdaXdJx7uX+0q6EfausHqQW+u+9393PcfTtwPfBld7+h0+uZHB8jG2XqpmWjDJPjY4napKGT623V197dW5dNX6tWNU6OjxENdT9U476eaYxFmhq369Jzz1pTX+22P+m+l2Scu3E8xdGrY31QDPx9+BO7RjmwZwejuSxG+a6Oxjdo4rTpVW1r7evmiR1103PZiE0bn97hc9mIGy7ZxmjlDKd6dpbLRmwejjDKd6LkslHbGid2jTJ17U5y2ahu+qaNmaXlMw2/D847exO3XHfhsmWGo6GlZXLZiOGofles/l5J8nrWjgWU73CpFQ0tn1atvZXNw/XjV7v8xozV/TwcDXHDJdvYPBw1bWNWbtNqnD/xe69cFvq1/ZuVfyk0vpat9oW4r2srcfe5bh1PcfTqWB8Uqd6lk9Rq7tIREQlZP92lIyIifUKBLyISCAW+iEggFPgiIoFQ4IuIBEKBLyISCAW+iEggFPgiIoFQ4IuIBEKBLyISCAW+iEggFPgiIoFQ4IuIBEKBLyISCAW+iEggFPgiIoFQ4IuIBEKBLyISCAW+iEggFPgiIoFQ4IuIBEKBLyISCAW+iEggFPgiIoHYkFbHZvZM4CvAMyrrud3db0prfYPm0Ow8U9NzHF8ssCWXZXJ8jIldo70uqyNWu22dGpNBHdukdTe2v/ylI9zz6MKy5Qd1PNa7Xrwu5u7pdGxmwCZ3/7mZRcDXgHe6+32tlsnn8z4zM5NKPf3k0Ow8+w8epVAsLU3LRhkO7Nkx8AfiaretU2MyqGObtO5m7RtlowxvvGiUzx6ZH7jxWO86uZ+a2RF3z8dpm9olHS/7eeXHqPKVzm+XATM1PbfsQC0US0xNz/Woos5Z7bZ1akwGdWyT1t2sfaNCscRth48N5Hisd73aT1O9hm9mGTN7AHgcuNvdDzdps8/MZsxsZmFhIc1y+sbxxUKi6YNktdvWqTEZ1LFNWnfc7Sm1+Au+38djvevVfppq4Lt7yd0vBM4BLjazC5q0udXd8+6eHxkZSbOcvrEll000fZCsdts6NSaDOrZJ6467PRmzNS0v6ejVftqVu3TcfRG4B/j1bqyv302Oj5GNMnXTslGGyfGxHlXUOavdtk6NyaCObdK6m7VvlI0y7N29dSDHY73r1X6a5l06I0DR3RfNLAu8FvjjtNY3SKpvyqzHOydWu22dGpNBHdukdTdr3+ounfwLzxq48VjverWfpnmXzsuBjwEZyn9JfNrd37/SMqHcpSMi0ilJ7tJJ7Qzf3R8CdqXVv4iIJKNP2oqIBEKBLyISCAW+iEggFPgiIoFQ4IuIBCK12zJXw8wWgB90uNvnAT/pcJ/dMIh1D2LNoLq7bRDr7ueaX+jusR5T0FeBnwYzm4l7j2o/GcS6B7FmUN3dNoh1D2LNzeiSjohIIBT4IiKBCCHwb+11Aas0iHUPYs2gurttEOsexJqXWffX8EVEpCyEM3wREWGdBX7lf9iaNbPPN5n3DDP7lJl9x8wOm9n27le4XJua32xmC2b2QOXrrb2osZGZfd/MjlZqWvZ4Uyv7UGWsHzKzV/SizkYx6r7MzE7UjPcf9qLORmaWM7PbzexRM/ummb2yYX7fjXeMmvturM1srKaeB8zsZ2b2roY2fTfWSaT2tMweeSfwTeBXmsz7F8CT7v4SM7ue8rP5r+tmcS2sVDPAp9z9X3exnrgud/dW9yW/Djiv8rUb+HDl336wUt0AX3X3q7pWTTx/Ctzl7teY2UZguGF+P453u5qhz8ba3eeAC6F8IgbMA3c0NOvHsY5t3Zzhm9k5wG8CH23R5A2Un88PcDtwhVmL//+tS2LUPKjeAPxl5T+yvw/ImdkLel3UIDKz5wCvBv4cwN2fqvwPcrX6arxj1tzvrgC+6+6NHwTtq7FOat0EPnAL8AfAmRbzR4FjAO5+GjgBPLc7pbXUrmaAN1b+dLzdzLZ2qa52HPiSmR0xs31N5i+NdcUPK9N6rV3dAK80swfN7K/N7PxuFtfCi4AF4C8ql/4+amabGtr023jHqRn6b6xrXQ/c1mR6v411Iusi8M3sKuBxdz/S61riilnz54Dt7v5y4G6e/gul137V3V9B+c/bt5vZq3tdUEzt6r6f8sfUdwJ/BhzqdoFNbABeAXzY3XcBJ4F397aktuLU3I9jDUDlEtTVwGd6XUunrYvABy4Frjaz7wN/BbzGzD7e0GYe2ApgZhuA5wA/7WaRDdrW7O4/dfdfVn78KHBRd0tszt3nK/8+Tvka58UNTZbGuuKcyrSeale3u//M3X9e+f6LQGRmz+t6ofV+CPzQ3Q9Xfr6dcpjW6rfxbltzn4511euA+939x03m9dtYJ7IuAt/d97v7Oe6+nfKfYl929xsamt0J/E7l+2sqbXr2IYQ4NTdcG7ya8pu7PWVmm8zs2dXvgSuBhxua3Qn8duWOhkuAE+7+oy6XWidO3Wb2j6rv65jZxZSPj16eFODufw8cM7OxyqQrgL9taNZX4x2n5n4c6xp7aX45B/psrJNab3fp1DGz9wMz7n4n5TeQ/peZfQd4gnLI9p2Gmv+NmV0NnKZc85t7WVvF84E7KsfqBuCT7n6Xmf0+gLv/d+CLwG8A3wFOAW/pUa214tR9DfA2MzsNFIDre3lSUOMdwCcqlxq+B7xlAMa7Xc19OdaVk4HXAv+yZlq/j3Vs+qStiEgg1sUlHRERaU+BLyISCAW+iEggFPgiIoFQ4IuIBEKBL+uGmZUqTzl82Mw+Y2bNHtgVt6/LrPIEUzO72sxafrq18mTIf7WKdbzXzP79amsUSUqBL+tJwd0vdPcLgKeA36+dWfmwTOJ93t3vdPcPrNAkByQOfJFuU+DLevVV4CVmtt3M5szsLyl/snarmV1pZvea2f2VvwSeBWBmv27l57ffD+ypdmTl/5fgv1W+f76Z3VF56NeDZvYq4APAuZW/LqYq7SbN7BuVB9+9r6av/2Rm3zKzrwFjiHTRuv6krYSp8qyk1wF3VSadB/yOu99XeV7Le4Bfc/eTZvYfgBvN7D8DHwFeQ/lTlJ9q0f2HgL9x99+y8jPTn0X5wWAXuHv1WepXVtZ5MWDAnZUHtZ2k/AnvCykfe/cDA/PAPxl8CnxZT7Jm9kDl+69SfpzGFuAHlWeXA1wCvAz4euUxCxuBe4GXAn/n7t8GqDzIrtkjlF8D/DaAu5eAE2a2uaHNlZWv2crPz6L8C+DZwB3ufqqyjjvXtLUiCSnwZT0pVM+yqyqhfrJ2EnC3u+9taFe33BoZcMDd/0fDOt7Vor1IV+gavoTmPuBSM3sJLD1F8x8DjwLbzezcSru9LZb/P8DbKstmrPy/O/0D5bP3qmngd2veGxg1s7OBrwATZpatPLnz9R3eNpEVKfAlKO6+QPmpo7eZ2UNULue4+y8oX8L5QuVN28dbdPFO4HIzO0r5+vvL3P2nlC8RPWxmU+7+JeCTwL2VdrcDz3b3+ym/N/Ag8NfAN1LbUJEm9LRMEZFA6AxfRCQQCnwRkUAo8EVEAqHAFxEJhAJfRCQQCnwRkUAo8EVEAqHAFxEJxP8HjxO+5SWltsIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Evaluate linear regression model \n",
    "y_pred = np.matmul(X_test,w)\n",
    "print(X_test.shape,w.shape,y_pred.shape)\n",
    "\n",
    "print(X_test[0])\n",
    "print(w)\n",
    "print(y_pred[0])\n",
    "\n",
    "\n",
    "print(\"Correlation coefficient:\", np.corrcoef(y_pred,y_test)[0,1])\n",
    "\n",
    "# Prepare scatter plot\n",
    "plt.scatter(y_pred,y_test)\n",
    "plt.xlabel(\"Predicted\")\n",
    "plt.ylabel(\"True\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "Exercise_3_2_solution",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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