decision-tree-classifier.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "55634ef8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-12T04:39:51.142648Z",
     "iopub.status.busy": "2024-08-12T04:39:51.142261Z",
     "iopub.status.idle": "2024-08-12T04:39:54.329654Z",
     "shell.execute_reply": "2024-08-12T04:39:54.328223Z"
    },
    "papermill": {
     "duration": 3.19437,
     "end_time": "2024-08-12T04:39:54.332462",
     "exception": false,
     "start_time": "2024-08-12T04:39:51.138092",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from sklearn import metrics\n",
    "from sklearn import tree\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import classification_report, confusion_matrix, mean_squared_error\n",
    "from sklearn.inspection import DecisionBoundaryDisplay\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.decomposition import PCA\n",
    "import warnings\n",
    "import itertools\n",
    "import math\n",
    "from sympy import *\n",
    "from tabulate import tabulate\n",
    "from tqdm.notebook import tqdm\n",
    "\n",
    "render_graphs = True # want to see the graphs in output? change to True, else will hide all unimportant graphs\n",
    "show_detailed_output = False # want to see lots of text in output? change to True, else will hide all unimportant graphs\n",
    "\n",
    "df = pd.read_csv('/kaggle/input/breast-cancer/wisconsin.csv')\n",
    "df2 = df.drop('Class', axis=1).drop('Sample Code Number', axis=1).drop('Uniformity of Cell Shape', axis=1)\n",
    "\n",
    "# data_set = []\n",
    "# possibilities2 = combinations(df2.columns)\n",
    "# for pos in possibilities2:\n",
    "#     if len(pos) == 0: continue\n",
    "#     tmp_df = df2.iloc[:, pos]\n",
    "#     patients = []\n",
    "#     for _, patient in tmp_df.iterrows():\n",
    "#         col = []\n",
    "#         for _, df_cell_value in patient.items():\n",
    "#             col.append(df_cell_value)\n",
    "#         patients.append(col)\n",
    "#     data_set.append(patients)\n",
    "\n",
    "def combinations(original_list):\n",
    "    num_subsets = 2 ** len(original_list)\n",
    "    subsets = []\n",
    "    for subset_index in range(num_subsets):\n",
    "        subset = []\n",
    "        for index in range(len(original_list)):\n",
    "            if (subset_index & (1 << index)) != 0:\n",
    "                subset.append(original_list[index])\n",
    "        subsets.append(subset)\n",
    "    return subsets\n",
    "possibilities2 = combinations(df2.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "53658b0d",
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
    "execution": {
     "iopub.execute_input": "2024-08-12T04:39:54.339394Z",
     "iopub.status.busy": "2024-08-12T04:39:54.338361Z",
     "iopub.status.idle": "2024-08-12T04:39:55.849227Z",
     "shell.execute_reply": "2024-08-12T04:39:55.847652Z"
    },
    "papermill": {
     "duration": 1.516961,
     "end_time": "2024-08-12T04:39:55.851858",
     "exception": false,
     "start_time": "2024-08-12T04:39:54.334897",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-> Found 256 possibilities\n",
      "\n",
      "-> Running best 3 models...\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dcebb92d66e34a6b9c5a47bdce49182e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/256 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "-> Least AIC is -1241.47359936439 at ['Uniformity of Cell Size', 'Single Epithelial Cell Size']\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# DAY 8 - Making Decision Trees\n",
    "\n",
    "# n_classes = 2\n",
    "# plot_colors = \"ry\"\n",
    "# plot_step = 0.02\n",
    "\n",
    "# results = []\n",
    "# y = df[['Class']]\n",
    "\n",
    "# for X in possibilities2:\n",
    "#     print(X)\n",
    "#     X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.3,random_state=0)\n",
    "#     clf = DecisionTreeClassifier(max_depth=3).fit(X_train,y_train)\n",
    "#     tree.plot_tree(clf)\n",
    "#     results.append(clf.predict(X_test))\n",
    "#     print(\"Test - Accuracy :\", metrics.accuracy_score(y_test, clf.predict(X_test)))\n",
    "#     aic = calculate_AIC(len(X), )\n",
    "#     #print(\"Test - Confusion matrix :\", metrics.confusion_matrix(y_test, clf.predict(X_test)))\n",
    "\n",
    "print('-> Found', len(possibilities2), 'possibilities\\n')\n",
    "    \n",
    "least_aic = 100\n",
    "least_possibility = []\n",
    "least_possibilities = pd.DataFrame(columns=['Possibility', 'AIC'])\n",
    "least_possibilities_matrix = []\n",
    "least_possibilities_class = []\n",
    "\n",
    "if (show_detailed_output):\n",
    "    print('Running long process...\\n')\n",
    "\n",
    "def calculate_AIC(n,mse,num_parameters):\n",
    "    aic = n * log(mse) + 2 * num_parameters\n",
    "    return aic\n",
    "\n",
    "print('-> Running best 3 models...\\n')\n",
    "\n",
    "for i in tqdm(range(len(possibilities2))):\n",
    "    if (i == 66 or i == 10 or i == 34):\n",
    "        possibility = possibilities2[i]\n",
    "        if (show_detailed_output):\n",
    "            print(possibility)\n",
    "        Z = []\n",
    "        if (len(possibility) > 0):\n",
    "            strings = ()\n",
    "            for col in possibility:\n",
    "                strings = strings + (f'[\"{possibility[0]}\"]',)\n",
    "            string = \"+\".join(strings)\n",
    "            string = f'df2[{string}]'\n",
    "            exec(f'X = {string}')\n",
    "        else:\n",
    "            exec(f'X = df2')\n",
    "        \n",
    "        for j in range(len(df2)):\n",
    "            d = []\n",
    "            for col in df2.columns:\n",
    "                d.append(df2.loc[j][col])\n",
    "            Z += [d]\n",
    "\n",
    "        sc = StandardScaler()\n",
    "        sc.fit(X)\n",
    "        x = sc.transform(X)\n",
    "        X = Z\n",
    "        y = df[['Class']]\n",
    "        X_train, X_test, y_train, y_test = train_test_split(x, y, test_size = 0.3, random_state = 0)\n",
    "        lr = LogisticRegression()\n",
    "        lr.fit(X_train, y_train.values.ravel())\n",
    "        y_pred = lr.predict(X_test)\n",
    "        mse = mean_squared_error(y_test, y_pred) / 4\n",
    "        n = len(y_test)\n",
    "        num_parameters = len(lr.coef_[0]) + 1\n",
    "\n",
    "        aic = calculate_AIC(n, mse, num_parameters)\n",
    "\n",
    "        clf = DecisionTreeClassifier(max_depth=3).fit(X_train,y_train)\n",
    "                \n",
    "        accuracy = clf.score(X_train, y_train)\n",
    "        mse = 1 - accuracy\n",
    "        n = len(y_train)\n",
    "        num_parameters = clf.tree_.node_count\n",
    "        \n",
    "        aic = calculate_AIC(n, mse, num_parameters)\n",
    "        \n",
    "        tree.plot_tree(clf, fontsize = 6)\n",
    "        \n",
    "        if (show_detailed_output):\n",
    "            print(f\"Train Accuracy: {round(metrics.accuracy_score(y_train, clf.predict(X_train)) * 100, 5)}%\")\n",
    "            print(f\"Train Confusion matrix: {metrics.confusion_matrix(y_train, clf.predict(X_train))}\")\n",
    "            print(f\"Train Classificiation report: {metrics.classification_report(y_train, clf.predict(X_train))}\")\n",
    "            print(f\"Test Accuracy: {round(metrics.accuracy_score(y_test, clf.predict(X_test)) * 100, 5)}%\")\n",
    "            print(f\"Test Confusion matrix: {metrics.confusion_matrix(y_test,clf.predict(X_test))}\")\n",
    "            print(f\"Test Classification report: {metrics.classification_report(y_test, clf.predict(X_test))}\")\n",
    "            print(f'AIC: {aic}\\n')\n",
    "        \n",
    "        least_possibilities.loc[len(least_possibilities.index)] = [possibility, aic] \n",
    "\n",
    "        if (aic < least_aic):\n",
    "            least_aic = aic\n",
    "            least_possibility = possibility\n",
    "        \n",
    "        array = []\n",
    "        \n",
    "        count = 0\n",
    "        \n",
    "        y = df\n",
    "\n",
    "        one = df[possibility[0]][int(len(df[possibility[0]]) * 0.7):]\n",
    "        two = df[possibility[1]][int(len(df[possibility[1]]) * 0.7):]\n",
    "        \n",
    "        first_column = []\n",
    "        for i in one:\n",
    "            first_column.append(i)\n",
    "\n",
    "        second_column = []\n",
    "        for i in two:\n",
    "            second_column.append(i)\n",
    "\n",
    "        for i in y_test['Class']:\n",
    "            str = f'{i}{clf.predict(X_test)[count]}'\n",
    "            if (str == \"44\"):\n",
    "                classification = 0\n",
    "                # color = \"red\"\n",
    "                # color = \"mediumseagreen\"\n",
    "                color = \"purple\"\n",
    "            elif (str == \"42\"):\n",
    "                classification = 1\n",
    "                # color = \"blue\"\n",
    "                # color = \"crimson\"\n",
    "                color = \"black\"\n",
    "                \n",
    "            elif (str == \"24\"):\n",
    "                classification = 2\n",
    "                # color = \"green\"\n",
    "                color = \"red\"\n",
    "            elif (str == \"22\"):\n",
    "                classification = 3\n",
    "                # color = \"yellow\"\n",
    "                color = \"green\"\n",
    "            \n",
    "            array.append([first_column[count], second_column[count], i, clf.predict(X_test)[count], classification, color])\n",
    "            count = count + 1\n",
    "        \n",
    "        least_possibilities_class.append(array)        \n",
    "        least_possibilities_matrix.append(metrics.confusion_matrix(y_test,clf.predict(X_test)))\n",
    "\n",
    "if (show_detailed_output):\n",
    "    print('\\nFinished long process')\n",
    "print(f'\\n-> Least AIC is {least_aic} at {least_possibility}\\n')\n",
    "least_possibilities = least_possibilities.sort_values(by=['AIC'], ascending=True)\n",
    "if (show_detailed_output):\n",
    "    print(least_possibilities[:10])\n",
    "    print(least_possibilities_matrix[:10])\n",
    "    print(least_possibilities_class[:10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "bafdd976",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-08-12T04:39:55.860380Z",
     "iopub.status.busy": "2024-08-12T04:39:55.859859Z",
     "iopub.status.idle": "2024-08-12T04:40:02.608638Z",
     "shell.execute_reply": "2024-08-12T04:40:02.607495Z"
    },
    "papermill": {
     "duration": 6.756063,
     "end_time": "2024-08-12T04:40:02.611090",
     "exception": false,
     "start_time": "2024-08-12T04:39:55.855027",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# DAY 9 - Classification & PCA of best possibilities\n",
    "\n",
    "# print(least_possibilities[2:5]) # 66, 10, 34\n",
    "# print(least_possibilities_matrix[2:5])\n",
    "\n",
    "possibilities = []\n",
    "\n",
    "#for possibility in least_possibilities[2:5]['Possibility']:\n",
    "for possibility in least_possibilities['Possibility']:\n",
    "    possibilities.append(possibility)\n",
    "\n",
    "for i in range(len(possibilities)):\n",
    "    if (render_graphs):\n",
    "        # markers = ['o', 's', 'D', '^']\n",
    "        markers = ['o', 'o', '^', 'o']\n",
    "        labels = ['True Positive', 'False Positive', 'False Negative', 'True Negative']\n",
    "\n",
    "        possibility = possibilities[i]\n",
    "        matrix = least_possibilities_matrix[i]\n",
    "        withClass = least_possibilities_class[i]\n",
    "\n",
    "        fig, ax = plt.subplots()\n",
    "\n",
    "        for row in withClass:\n",
    "            x, y, _, _, classification, color = row\n",
    "            ax.scatter(x, y, marker=markers[classification], color=color, alpha=0.5, label=labels[classification])\n",
    "\n",
    "        handles, labels = ax.get_legend_handles_labels()\n",
    "        by_label = dict(zip(labels, handles))\n",
    "        ax.legend(by_label.values(), by_label.keys())\n",
    "        ax.set_xlabel(possibility[0])\n",
    "        ax.set_ylabel(possibility[1])\n",
    "        ax.set_title(f'Model Testing Set Results\\n{possibility[0]} x {possibility[1]}\\n')\n",
    "        plt.show()\n",
    "        plt.close(fig)"
   ]
  }
 ],
 "metadata": {
  "kaggle": {
   "accelerator": "none",
   "dataSources": [
    {
     "datasetId": 5407357,
     "sourceId": 8980061,
     "sourceType": "datasetVersion"
    }
   ],
   "dockerImageVersionId": 30746,
   "isGpuEnabled": false,
   "isInternetEnabled": true,
   "language": "python",
   "sourceType": "notebook"
  },
  "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": "3.10.13"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 14.871754,
   "end_time": "2024-08-12T04:40:03.338129",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2024-08-12T04:39:48.466375",
   "version": "2.5.0"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "2191c9d9ddd7474282f4c6892403b633": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
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