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Fake-Real-New-Classification
File size: 77,774 Bytes 
dfb3177
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Şerife GÖKDAŞ\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\xgboost\\core.py:158: UserWarning: [17:39:51] WARNING: C:\\buildkite-agent\\builds\\buildkite-windows-cpu-autoscaling-group-i-0c55ff5f71b100e98-1\\xgboost\\xgboost-ci-windows\\src\\learner.cc:740: \n",
      "Parameters: { \"use_label_encoder\" } are not used.\n",
      "\n",
      "  warnings.warn(smsg, UserWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "XGBoost Accuracy: 0.87\n",
      "\n",
      "Classification Report:\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.89      0.86      0.88      1301\n",
      "           1       0.86      0.89      0.87      1244\n",
      "\n",
      "    accuracy                           0.87      2545\n",
      "   macro avg       0.87      0.87      0.87      2545\n",
      "weighted avg       0.87      0.87      0.87      2545\n",
      "\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "['xgboost_model.pkl']"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import accuracy_score, classification_report, confusion_matrix, roc_auc_score, roc_curve\n",
    "import xgboost as xgb\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import joblib \n",
    "\n",
    "# Veriyi yükleme\n",
    "data = pd.read_csv('data_vectorized.csv')\n",
    "\n",
    "# Veriyi ayırma (özellikler ve etiketler)\n",
    "X = data.drop(columns=['Label'])  # Etiket hariç tüm sütunlar\n",
    "y = data['Label']  # Etiket\n",
    "\n",
    "# Veriyi eğitim ve test olarak ayırma\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "# XGBoost modelini oluşturma ve eğitim\n",
    "xgb_classifier = xgb.XGBClassifier(eval_metric='mlogloss', use_label_encoder=False, random_state=42)\n",
    "xgb_classifier.fit(X_train, y_train)\n",
    "\n",
    "# Test seti üzerinde tahmin yapma\n",
    "y_pred = xgb_classifier.predict(X_test)\n",
    "\n",
    "# Doğruluk hesaplama\n",
    "accuracy = accuracy_score(y_test, y_pred)\n",
    "print(f\"XGBoost Accuracy: {accuracy:.2f}\")\n",
    "\n",
    "# Precision, Recall, F1-Score\n",
    "print(\"\\nClassification Report:\")\n",
    "print(classification_report(y_test, y_pred))\n",
    "\n",
    "# Confusion Matrix\n",
    "conf_matrix = confusion_matrix(y_test, y_pred)\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.heatmap(conf_matrix, annot=True, fmt='d', cmap='Blues', xticklabels=[\"Class 0\", \"Class 1\"], yticklabels=[\"Class 0\", \"Class 1\"])\n",
    "plt.title(\"XGBoost - Confusion Matrix\")\n",
    "plt.xlabel(\"Predicted\")\n",
    "plt.ylabel(\"Actual\")\n",
    "plt.show()\n",
    "\n",
    "# ROC-AUC Hesaplama ve Grafik\n",
    "if len(set(y_test)) == 2:  # İkili sınıflandırma kontrolü\n",
    "    roc_auc = roc_auc_score(y_test, xgb_classifier.predict_proba(X_test)[:, 1])  # Tahmin olasılıkları\n",
    "    fpr, tpr, thresholds = roc_curve(y_test, xgb_classifier.predict_proba(X_test)[:, 1])\n",
    "    plt.figure(figsize=(8, 6))\n",
    "    plt.plot(fpr, tpr, label=f\"ROC-AUC: {roc_auc:.2f}\")\n",
    "    plt.plot([0, 1], [0, 1], 'k--', label=\"Random Guess\")\n",
    "    plt.xlabel(\"False Positive Rate\")\n",
    "    plt.ylabel(\"True Positive Rate\")\n",
    "    plt.title(\"XGBoost - ROC Curve\")\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "\n",
    "# XGBoost modelini kaydetme\n",
    "joblib.dump(xgb_classifier, 'xgboost_model.pkl')  # Modeli kaydet\n"
   ]
  }
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