{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "00b7d3d0-65d5-46ec-b80c-1aca3085a908",
   "metadata": {},
   "outputs": [],
   "source": [
    "Mushroom Classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bd382933-9892-4c38-8231-d80df9c7bc86",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>class=e</th>\n",
       "      <th>class=p</th>\n",
       "      <th>cap-shape=b</th>\n",
       "      <th>cap-shape=c</th>\n",
       "      <th>cap-shape=f</th>\n",
       "      <th>cap-shape=k</th>\n",
       "      <th>cap-shape=s</th>\n",
       "      <th>cap-shape=x</th>\n",
       "      <th>cap-surface=f</th>\n",
       "      <th>cap-surface=g</th>\n",
       "      <th>...</th>\n",
       "      <th>population=s</th>\n",
       "      <th>population=v</th>\n",
       "      <th>population=y</th>\n",
       "      <th>habitat=d</th>\n",
       "      <th>habitat=g</th>\n",
       "      <th>habitat=l</th>\n",
       "      <th>habitat=m</th>\n",
       "      <th>habitat=p</th>\n",
       "      <th>habitat=u</th>\n",
       "      <th>habitat=w</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 119 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   class=e  class=p  cap-shape=b  cap-shape=c  cap-shape=f  cap-shape=k  \\\n",
       "0        0        1            0            0            0            0   \n",
       "1        1        0            0            0            0            0   \n",
       "2        1        0            1            0            0            0   \n",
       "3        0        1            0            0            0            0   \n",
       "4        1        0            0            0            0            0   \n",
       "\n",
       "   cap-shape=s  cap-shape=x  cap-surface=f  cap-surface=g  ...  population=s  \\\n",
       "0            0            1              0              0  ...             1   \n",
       "1            0            1              0              0  ...             0   \n",
       "2            0            0              0              0  ...             0   \n",
       "3            0            1              0              0  ...             1   \n",
       "4            0            1              0              0  ...             0   \n",
       "\n",
       "   population=v  population=y  habitat=d  habitat=g  habitat=l  habitat=m  \\\n",
       "0             0             0          0          0          0          0   \n",
       "1             0             0          0          1          0          0   \n",
       "2             0             0          0          0          0          1   \n",
       "3             0             0          0          0          0          0   \n",
       "4             0             0          0          1          0          0   \n",
       "\n",
       "   habitat=p  habitat=u  habitat=w  \n",
       "0          0          1          0  \n",
       "1          0          0          0  \n",
       "2          0          0          0  \n",
       "3          0          1          0  \n",
       "4          0          0          0  \n",
       "\n",
       "[5 rows x 119 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "\n",
    "# CSV dosyasını oku\n",
    "df = pd.read_csv('mushroom.csv')\n",
    "\n",
    "# İlk birkaç satırı göster\n",
    "df.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4d00275-2011-4f70-970e-f3f94e3b6d71",
   "metadata": {},
   "source": [
    "## 1. Hedef Değişkeni Belirleyelim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e46f144e-a279-435a-b23a-9d1df8f432b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['target'] = df['class=p']  # Zehirli olanlar 1, yenilebilir olanlar 0\n",
    "X = df.drop(['class=e', 'class=p', 'target'], axis=1)\n",
    "y = df['target']\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e04c4de4-992c-44f6-856f-6948b606c4da",
   "metadata": {},
   "source": [
    "## 2. Veriyi Eğitim ve Test Olarak Ayır"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2ee13273-e098-4431-a319-819561fd84e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8822a86-fdbc-40c5-a291-5f6136b44e80",
   "metadata": {},
   "source": [
    "## 3. Model Eğitimi (Örnek: Karar Ağacı)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ede5451d-283c-41c1-8ceb-908976b4e520",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Doğruluk: 1.0\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      1.00      1.00       843\n",
      "           1       1.00      1.00      1.00       782\n",
      "\n",
      "    accuracy                           1.00      1625\n",
      "   macro avg       1.00      1.00      1.00      1625\n",
      "weighted avg       1.00      1.00      1.00      1625\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.metrics import accuracy_score, classification_report\n",
    "\n",
    "clf = DecisionTreeClassifier()\n",
    "clf.fit(X_train, y_train)\n",
    "\n",
    "y_pred = clf.predict(X_test)\n",
    "\n",
    "print(\"Doğruluk:\", accuracy_score(y_test, y_pred))\n",
    "print(classification_report(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d98dafd2-38ad-4ff5-af03-8417b63e4d0a",
   "metadata": {},
   "source": [
    "##  Karar Ağacını Görselleştirme"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9c3d59fd-4e27-485d-9e69-84b1ae794b39",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Modelin nasıl karar verdiğini anlamak için:\n",
    "from sklearn.tree import plot_tree\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(figsize=(20,10))\n",
    "plot_tree(clf, filled=True, max_depth=2, feature_names=X.columns)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a9f34cf-ed40-494f-9a8a-646d1afc2745",
   "metadata": {},
   "source": [
    "## Çapraz Doğrulama (Cross Validation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4b94d5f4-c84a-4284-baac-3d40fd4f6083",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5 Katlı Çapraz Doğrulama Ortalaması: 0.966256612353164\n"
     ]
    }
   ],
   "source": [
    "# Modelin genellenebilirliğini ölçmek için\n",
    "from sklearn.model_selection import cross_val_score\n",
    "scores = cross_val_score(clf, X, y, cv=5)\n",
    "print(\"5 Katlı Çapraz Doğrulama Ortalaması:\", scores.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c93e3ba-924c-45e1-8114-497343f6b7fb",
   "metadata": {},
   "source": [
    "## Önemli Özellikleri Görmek (Feature Importance)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "74f44e50-6203-4b5f-940d-0890421b32a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "odor=n: 0.6231\n",
      "stalk-root=c: 0.1800\n",
      "stalk-surface-below-ring=y: 0.0936\n",
      "spore-print-color=r: 0.0341\n",
      "odor=a: 0.0208\n",
      "odor=l: 0.0207\n",
      "habitat=d: 0.0178\n",
      "stalk-color-above-ring=n: 0.0056\n",
      "cap-surface=g: 0.0018\n",
      "population=c: 0.0018\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "importances = clf.feature_importances_\n",
    "indices = np.argsort(importances)[-10:]  # en önemli 10 özelliği al\n",
    "\n",
    "for i in reversed(indices):\n",
    "    print(f\"{X.columns[i]}: {importances[i]:.4f}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e38b1aea-b631-40f6-9217-f9fa536baa7f",
   "metadata": {},
   "source": [
    " ## En Önemli 10 Özellik"
   ]
  },
  {
   "cell_type": "raw",
   "id": "8ff459f3-97d5-4abb-b6dd-e298ed3c72ee",
   "metadata": {},
   "source": [
    "Özellik\tÖnem Skoru\n",
    "odor=n (koku)\t0.6231\n",
    "stalk-root=c\t0.1800\n",
    "stalk-surface-below-ring=y\t0.0936\n",
    "spore-print-color=r\t0.0411\n",
    "odor=a\t0.0280\n",
    "odor=l\t0.0207\n",
    "habitat=d\t0.0174\n",
    "stalk-color-above-ring=n\t0.0056\n",
    "cap-surface=f\t0.0018\n",
    "population=c\t0.0018"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1565c36-701a-4bf6-92e2-963b7ec57e28",
   "metadata": {},
   "source": [
    "## Yorum\n",
    "### Özellikle odor=n (koku yok) özelliği, zehirli/yenilebilir ayrımında açık ara en belirleyici özellik.\n",
    "\n",
    "### stalk-root, spore-print-color, habitat, cap-surface gibi morfolojik özellikler de etkili ama daha az derecede.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6e7cc021-7264-4b13-82e3-eec8bc159048",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['class=e', 'class=p', 'cap-shape=b', 'cap-shape=c', 'cap-shape=f',\n",
      "       'cap-shape=k', 'cap-shape=s', 'cap-shape=x', 'cap-surface=f',\n",
      "       'cap-surface=g',\n",
      "       ...\n",
      "       'population=s', 'population=v', 'population=y', 'habitat=d',\n",
      "       'habitat=g', 'habitat=l', 'habitat=m', 'habitat=p', 'habitat=u',\n",
      "       'habitat=w'],\n",
      "      dtype='object', length=119)\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv(\"mushroom.csv\")\n",
    "print(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d8ca75df-2d31-4ee4-a1d5-59ac8ced0458",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "351a40b1-47a4-49b9-9d4a-76662afbe62f",
   "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": "3.12.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}