svm.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4.4 Construção do modelo SVM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Bibliotecas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from sklearn.svm import SVC\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.metrics import confusion_matrix, precision_score, recall_score, f1_score, accuracy_score\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.model_selection import train_test_split\n",
    "from imblearn.under_sampling import RandomUnderSampler"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('data/proposicoes_ord_2013-2023.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['idProposicao'] = df['idProposicao'].astype('str')\n",
    "colunas = [col for col in df.columns if col != 'VirouLei'] + ['VirouLei']\n",
    "df = df.reindex(columns=colunas)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df.select_dtypes(include=['int64', 'float64'])\n",
    "y = X['VirouLei']\n",
    "X = X.drop(columns=['Ano','VirouLei'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      Administração e Políticas Públicas  Desenvolvimento Social e Urbano  \\\n",
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     "execution_count": 5,
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    }
   ],
   "source": [
    "X"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Undersampling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      Administração e Políticas Públicas  Desenvolvimento Social e Urbano  \\\n",
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     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "undersample = RandomUnderSampler()\n",
    "X_resampled, y_resampled = undersample.fit_resample(X, y)\n",
    "X_resampled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "RANDOM_STATE=2\n",
    "BATCH_SIZE=10\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X_resampled, y_resampled, random_state=RANDOM_STATE, test_size=0.2)\n",
    "X_train, X_val, y_train, y_val = train_test_split(X_train, y_train, random_state=RANDOM_STATE, test_size=0.2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Regularização dos parâmetros $ C\\; \\text{e}\\; \\gamma$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acurácia média com diferentes kernels:\n",
      "linear: 59.11%\n",
      "rbf: 61.68%\n",
      "poly: 56.80%\n"
     ]
    }
   ],
   "source": [
    "kernels = ['linear', 'rbf', 'poly']\n",
    "results = {}\n",
    "\n",
    "for kernel in kernels:\n",
    "    svc = SVC(kernel=kernel, gamma='auto') \n",
    "    cv_result = cross_val_score(svc, X_resampled, y_resampled, cv=10, scoring='accuracy')\n",
    "    results[kernel] = cv_result.mean() * 100\n",
    "\n",
    "print(\"Acurácia média com diferentes kernels:\")\n",
    "for kernel, score in results.items():\n",
    "    print(f\"{kernel}: {score:.2f}%\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Melhores parâmetros para o kernel RBF: {'C': 0.1, 'gamma': 'scale'}\n",
      "Acurácia média: 0.6054217189252711\n"
     ]
    }
   ],
   "source": [
    "param_grid = {\n",
    "    'C': [0.1, 1, 10, 100],\n",
    "    'gamma': ['scale', 'auto']\n",
    "}\n",
    "\n",
    "grid_search = GridSearchCV(SVC(kernel='rbf'), param_grid, cv=5, scoring='accuracy')\n",
    "grid_search.fit(X_train, y_train)\n",
    "\n",
    "print(\"Melhores parâmetros para o kernel RBF:\", grid_search.best_params_)\n",
    "print(\"Acurácia média:\", grid_search.best_score_)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acurácia no treino: 0.612603305785124\n",
      "Acurácia no teste: 0.6633663366336634\n",
      "E_in: 0.387396694214876\n",
      "E_out: 0.3366336633663366\n"
     ]
    }
   ],
   "source": [
    "svc = SVC(gamma=\"auto\", class_weight='balanced', kernel=\"rbf\", random_state=42)\n",
    "\n",
    "svc.fit(X_train, y_train)\n",
    "y_pred = svc.predict(X_test)\n",
    "print('Acurácia no treino:', svc.score(X_train, y_train))\n",
    "print('Acurácia no teste:', svc.score(X_test, y_test))\n",
    "\n",
    "print('E_in:', 1 - svc.score(X_train, y_train))\n",
    "print('E_out:', 1 - svc.score(X_test, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Precisão: 0.664547616457093\n",
      "Recall: 0.6633663366336634\n",
      "F1 Score: 0.6636971480166886\n",
      "\n",
      "Relatório de Classificação:\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "           0       0.63      0.66      0.65       141\n",
      "           1       0.69      0.67      0.68       162\n",
      "\n",
      "    accuracy                           0.66       303\n",
      "   macro avg       0.66      0.66      0.66       303\n",
      "weighted avg       0.66      0.66      0.66       303\n",
      "\n"
     ]
    }
   ],
   "source": [
    "precision = precision_score(y_test, y_pred, average='weighted')\n",
    "recall = recall_score(y_test, y_pred, average='weighted')\n",
    "f1 = f1_score(y_test, y_pred, average='weighted')\n",
    "\n",
    "print('Precisão:', precision)\n",
    "print('Recall:', recall)\n",
    "print('F1 Score:', f1)\n",
    "\n",
    "print(\"\\nRelatório de Classificação:\\n\", classification_report(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cm = confusion_matrix(y_test, y_pred)\n",
    "plt.figure(figsize=(10, 7))\n",
    "sns.heatmap(cm, annot=True, fmt='d', cmap='Blues')\n",
    "plt.xlabel('Predição')\n",
    "plt.ylabel('Valores Reais')\n",
    "plt.title('Matriz de Confusão com undersampling')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plotagem dos vetores de suporte"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "\n",
    "pca = PCA(n_components=2)\n",
    "X_train_pca = pca.fit_transform(X_train)\n",
    "\n",
    "svc = SVC(kernel='linear')\n",
    "svc.fit(X_train_pca, y_train)\n",
    "\n",
    "def plot_svc_decision_function(model, X_train):\n",
    "    xlim = (X_train[:, 0].min() - 1, X_train[:, 0].max() + 1)\n",
    "    ylim = (X_train[:, 1].min() - 1, X_train[:, 1].max() + 1)\n",
    "    \n",
    "    x = np.linspace(xlim[0], xlim[1], 30)\n",
    "    y = np.linspace(ylim[0], ylim[1], 30)\n",
    "    Y, X = np.meshgrid(y, x)\n",
    "    xy = np.vstack([X.ravel(), Y.ravel()]).T\n",
    "    P = model.decision_function(xy).reshape(X.shape)\n",
    "\n",
    "    plt.contour(X, Y, P, colors='k', levels=[-1, 0, 1], alpha=0.5, linestyles=['--', '-', '--'])\n",
    "\n",
    "plt.scatter(X_train_pca[:, 0], X_train_pca[:, 1], c=y_train, s=50, cmap='autumn')\n",
    "plot_svc_decision_function(svc, X_train_pca)\n",
    "\n",
    "plt.scatter(svc.support_vectors_[:, 0], svc.support_vectors_[:, 1], s=10, linewidth=10, facecolors='k')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Número de vetores de suporte: 818\n"
     ]
    }
   ],
   "source": [
    "num_support_vectors = len(svc.support_)\n",
    "print(f'Número de vetores de suporte: {num_support_vectors}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pca = PCA(n_components=3)\n",
    "X_train_pca = pca.fit_transform(X_train)\n",
    "\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "scatter = ax.scatter(X_train_pca[:, 0], X_train_pca[:, 1], X_train_pca[:, 2], c=y_train, cmap='viridis')\n",
    "ax.set_xlabel('Componente Principal 1')\n",
    "ax.set_ylabel('Componente Principal 2')\n",
    "ax.set_zlabel('Componente Principal 3')\n",
    "cbar = plt.colorbar(scatter)\n",
    "cbar.set_label('Rótulos')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Conclusão: O modelo SVM apresenta um número elevado de vetores de suporte, o que indica que ele pode estar capturando excessivamente as variações e o \"ruído\" nos dados de treinamento. Esse comportamento sugere um ajuste excessivo (overfitting), onde o modelo se adapta demais aos dados, comprometendo sua capacidade de generalização. Além disso, a natureza dos dados, que parecem ser fortemente não linearmente separáveis, pode estar contribuindo para essa situação. "
   ]
  }
 ],
 "metadata": {
  "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",
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