cas-pml/SL/aufgaben/template/4_WS/Loesungen/WS 13 Loesung.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# WS 13 Kreuzvalidierung"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* vergleichen Sie alle bisher bekannten Klassifikatoren (ausser SVC und MLPClassifier) in Bezug auf deren Stabilität unter Anwendung von Kreuzvalidierung\n",
    "* verwenden Sie für die Klassifikatoren jeweils Default-Parametrisierung\n",
    "* setzen Sie für die Kreuzvalidierung folgende Funktion ein: `sklearn.model_selection.cross_val_score`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "## load libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns; sns.set()\n",
    "\n",
    "## load data\n",
    "datapath = '../../3_data'\n",
    "from os import chdir; chdir(datapath)\n",
    "bank_df = pd.read_csv('bank_data_prep.csv')\n",
    "\n",
    "## features - target - tplit\n",
    "X = bank_df.drop('y', axis=1)\n",
    "y = bank_df['y']\n",
    "\n",
    "## train - test - split\n",
    "## obsolete here, is done internally by cross validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "KNeighborsClassifier\n",
      "DecisionTreeClassifier\n",
      "RandomForestClassifier\n",
      "AdaBoostClassifier\n",
      "GradientBoostingClassifier\n",
      "HistGradientBoostingClassifier\n",
      "CatBoostClassifier\n",
      "LGBMClassifier\n",
      "LinearDiscriminantAnalysis\n",
      "QuadraticDiscriminantAnalysis\n",
      "GaussianNB\n",
      "LogisticRegression\n"
     ]
    }
   ],
   "source": [
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.ensemble import AdaBoostClassifier\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "from sklearn.ensemble import HistGradientBoostingClassifier\n",
    "from catboost import CatBoostClassifier\n",
    "from lightgbm.sklearn import LGBMClassifier\n",
    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n",
    "from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "from sklearn.model_selection import cross_val_score\n",
    "\n",
    "models = [\n",
    "    KNeighborsClassifier(),\n",
    "    DecisionTreeClassifier(),\n",
    "    RandomForestClassifier(),\n",
    "    AdaBoostClassifier(),\n",
    "    GradientBoostingClassifier(),\n",
    "    HistGradientBoostingClassifier(),\n",
    "    CatBoostClassifier(logging_level='Silent'), ## optional\n",
    "    LGBMClassifier(), ## optional\n",
    "    LinearDiscriminantAnalysis(),\n",
    "    QuadraticDiscriminantAnalysis(),\n",
    "    GaussianNB(),\n",
    "    LogisticRegression()\n",
    "]\n",
    "\n",
    "kfold = 5\n",
    "model_names = []\n",
    "model_scores = []\n",
    "\n",
    "for model in models:\n",
    "    model_name = model.__class__.__name__\n",
    "    print(model_name)\n",
    "    scores = cross_val_score(model, X, y, cv=kfold, n_jobs=-1)\n",
    "    for i in range(len(scores)):\n",
    "        model_scores.append(scores[i])\n",
    "        model_names.append(model_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\werne\\anaconda3\\Lib\\site-packages\\seaborn\\_oldcore.py:1765: FutureWarning: unique with argument that is not not a Series, Index, ExtensionArray, or np.ndarray is deprecated and will raise in a future version.\n",
      "  order = pd.unique(vector)\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## manage results, e.g. in pandas dataframe\n",
    "res_df = pd.DataFrame({\n",
    "    'names' : model_names,\n",
    "    'scores' : model_scores\n",
    "})\n",
    "\n",
    "## visualize results\n",
    "sns.boxplot(x=model_scores, y=model_names, color='steelblue');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Fazit:**\n",
    "* am besten sind die Ensemble Methoden\n",
    "* die Stabilität ist bei allen in derselben Grössenordnung"
   ]
  }
 ],
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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  "toc": {
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   "title_cell": "WS 16 Validierung - Kreuzvalidierung",
   "title_sidebar": "Contents",
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    "height": "calc(100% - 180px)",
    "left": "10px",
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    }
   },
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 },
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}