E2/.ipynb_checkpoints/Digits_Classification-checkpoint.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploration 2-3\n",
    "### Digits Classifier\n",
    "\n",
    "### Table of Contents\n",
    "    1.Data Definition\n",
    "    2.EDA\n",
    "        t-SNE\n",
    "    3.Model Training\n",
    "    4.Model Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.datasets import load_digits\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 데이터 준비"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "digits_db = load_digits()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "와인 데이터 셋의 키: \n",
      "dict_keys(['data', 'target', 'frame', 'feature_names', 'target_names', 'images', 'DESCR'])\n"
     ]
    }
   ],
   "source": [
    "print(\"와인 데이터 셋의 키: \\n{}\".format(digits_db.keys()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".. _digits_dataset:\n",
      "\n",
      "Optical recognition of handwritten digits dataset\n",
      "--------------------------------------------------\n",
      "\n",
      "**Data Set Characteristics:**\n",
      "\n",
      "    :Number of Instances: 5620\n",
      "    :Number of Attributes: 64\n",
      "    :Attribute Information: 8x8 image of integer pixels in the range 0..16.\n",
      "    :Missing Attribute Values: None\n",
      "    :Creator: E. Alpaydin (alpaydin '@' boun.edu.tr)\n",
      "    :Date: July; 1998\n",
      "\n",
      "This is a copy of the test set of the UCI ML hand-written digits datasets\n",
      "https://archive.ics.uci.edu/ml/datasets/Optical+Recognition+of+Handwritten+Digits\n",
      "\n",
      "The data set contains images of hand-written digits: 10 classes where\n",
      "each class refers to a digit.\n",
      "\n",
      "Preprocessing programs made available by NIST were used to extract\n",
      "normalized bitmaps of handwritten digits from a preprinted form. From a\n",
      "total of 43 people, 30 contributed to the training set and different 13\n",
      "to the test set. 32x32 bitmaps are divided into nonoverlapping blocks of\n",
      "4x4 and the number of on pixels are counted in each block. This generates\n",
      "an input matrix of 8x8 where each element is an integer in the range\n",
      "0..16. This reduces dimensionality and gives invariance to small\n",
      "distortions.\n",
      "\n",
      "For info on NIST preprocessing routines, see M. D. Garris, J. L. Blue, G.\n",
      "T. Candela, D. L. Dimmick, J. Geist, P. J. Grother, S. A. Janet, and C.\n",
      "L. Wilson, NIST Form-Based Handprint Recognition System, NISTIR 5469,\n",
      "1994.\n",
      "\n",
      ".. topic:: References\n",
      "\n",
      "  - C. Kaynak (1995) Methods of Combining Multiple Classifiers and Their\n",
      "    Applications to Handwritten Digit Recognition, MSc Thesis, Institute of\n",
      "    Graduate Studies in Science and Engineering, Bogazici University.\n",
      "  - E. Alpaydin, C. Kaynak (1998) Cascading Classifiers, Kybernetika.\n",
      "  - Ken Tang and Ponnuthurai N. Suganthan and Xi Yao and A. Kai Qin.\n",
      "    Linear dimensionalityreduction using relevance weighted LDA. School of\n",
      "    Electrical and Electronic Engineering Nanyang Technological University.\n",
      "    2005.\n",
      "  - Claudio Gentile. A New Approximate Maximal Margin Classification\n",
      "    Algorithm. NIPS. 2000.\n"
     ]
    }
   ],
   "source": [
    "print(digits_db.DESCR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 실제 데이터는 data 필드에 저장되어 있음\n",
    "digits_data = digits_db.data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1797, 64)\n"
     ]
    }
   ],
   "source": [
    "print(digits_data.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "digits_target = digits_db.target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1797,)\n"
     ]
    }
   ],
   "source": [
    "print(digits_target.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_names = digits_db.feature_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "digits_df = pd.DataFrame(digits_data, columns=feature_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "digits_df['label'] = digits_target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
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      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "digits_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in range(10):\n",
    "    plt.subplot(2, 5, i + 1)\n",
    "    plt.imshow(digits.data[i].reshape(8, 8), cmap='gray')\n",
    "    plt.axis('off')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.manifold import TSNE\n",
    "\n",
    "# t-SNE 모델 생성 및 학습\n",
    "# 시각화"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "plt.figure(figsize=(20,20))\n",
    "# PCA 모델을 생성\n",
    "pca = PCA(n_components=2) # 주성분 갯수\n",
    "pca.fit(digits.data) # PCA 적용\n",
    "\n",
    "\n",
    "# 두 개의 주성분으로 숫자 데이터를 변환\n",
    "digits_pca = pca.transform(digits.data) \n",
    "\n",
    "color_list = ['#1abc9c','#2ecc71','#3498db','#9b59b6','#34495e',\n",
    "             '#16a085','#27ae60','#e67e22','#e74c3c','#2c3e50']\n",
    "\n",
    "\n",
    "for i in range(len(digits_db.data)): # digits.data의 길이까지 정수 갯수\n",
    "\n",
    "    # 숫자 텍스트를 이용해 산점도 그리기\n",
    "    plt.text(digits_pca[i, 0], digits_pca[i, 1], str(digits.target[i]), # x, y, 그룹; str은 문자로 변환\n",
    "             color=color_list[digits_db.target[i]], # 산점도 색상\n",
    "             fontdict={'weight':'bold', 'size':9}) # font 설정\n",
    "\n",
    "plt.xlim(digits_pca[:, 0].min(), digits_pca[:,1].max()) # 최소, 최대\n",
    "plt.ylim(digits_pca[:, 1].min(), digits_pca[:,1].max()) # 최소, 최대\n",
    "plt.xlabel('first principle component') # x 축 이름\n",
    "plt.ylabel('second principle component') # y 축 이름\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 훈련 / 테스트 데이터 준비 및 모델링"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X = digits_df.drop('label', axis=1)\n",
    "y = digits_df['label']\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, \n",
    "                                                    y, \n",
    "                                                    test_size=0.2, \n",
    "                                                    random_state=7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X_train의 크기: (1437, 64)\n",
      "y_train의 크기: (1437, 64)\n"
     ]
    }
   ],
   "source": [
    "print(\"X_train의 크기: {}\".format(X_train.shape))\n",
    "print(\"y_train의 크기: {}\".format(X_train.shape))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X_test의 크기: (360, 64)\n",
      "y_test의 크기: (360,)\n"
     ]
    }
   ],
   "source": [
    "print(\"X_test의 크기: {}\".format(X_test.shape))\n",
    "print(\"y_test의 크기: {}\".format(y_test.shape))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LogisticRegression as lr\n",
    "from sklearn.linear_model import SGDClassifier as sgd\n",
    "from sklearn.svm import SVC as svm\n",
    "from sklearn.tree import DecisionTreeClassifier as dt\n",
    "from sklearn.ensemble import RandomForestClassifier as rf\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.model_selection import cross_val_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "models = {\n",
    "    'DecisionTree': dt(),\n",
    "    'RandomForest': rf(),\n",
    "    'SVM': svm(),\n",
    "    'SGD': sgd(),\n",
    "    'Logistic Regression': lr()\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Decision Tree Pipeline\n",
    "pipeline_dt = Pipeline([('scaler1', StandardScaler()),\n",
    "                        (\"dt_classifier\", dt())]\n",
    "                        )\n",
    "# RandomForest Pipeline\n",
    "pipeline_rf = Pipeline([('scaler2', StandardScaler()),\n",
    "                        (\"rf_classifier\", rf())]\n",
    "                        )\n",
    "# SVM Pipeline\n",
    "pipeline_svm = Pipeline([('scaler3', StandardScaler()),\n",
    "                        (\"svm_classifier\", svm())]\n",
    "                        )\n",
    "# SGD Pipeline\n",
    "pipeline_sgd = Pipeline([('scaler4', StandardScaler()),\n",
    "                        (\"sgd_classifier\", sgd())]\n",
    "                        )\n",
    "# Logisitc Regression Pipeline\n",
    "pipeline_lr = Pipeline([('scaler5', StandardScaler()),\n",
    "                        (\"lr_classifier\", lr())]\n",
    "                        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "pipelines = [\n",
    "    pipeline_dt,\n",
    "    pipeline_rf,\n",
    "    pipeline_svm,\n",
    "    pipeline_sgd,\n",
    "    pipeline_lr\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "for pipe in pipelines:\n",
    "    pipe.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DecisionTree Test Accuracy: 70%\n",
      "RandomForest Test Accuracy: 92%\n",
      "SVM Test Accuracy: 95%\n",
      "SGD Test Accuracy: 92%\n",
      "Logistic Regression Test Accuracy: 94%\n"
     ]
    }
   ],
   "source": [
    "model_list = list(models.keys())\n",
    "test_scores = []\n",
    "\n",
    "for i, model in enumerate(pipelines):\n",
    "    score = cross_val_score(model, X_test, y_test, scoring='accuracy', cv=5)\n",
    "    score = np.mean(score)\n",
    "    score = int(round(score, 2) * 100)\n",
    "    test_scores.append(score)\n",
    "    print(\"{} Test Accuracy: {}%\".format(model_list[i], test_scores[i]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,7))\n",
    "sns.set_style('whitegrid')\n",
    "plt.title('Test Scores of Models')\n",
    "\n",
    "ax1 = sns.barplot(x=model_list, y=test_scores, alpha=0.7)\n",
    "for p in ax1.patches:\n",
    "    ax1.annotate(f'\\n{int(p.get_height())}%', (p.get_x()+0.4, p.get_height()), ha='center', va='top', color='white', size=20)\n",
    "    \n",
    "plt.xlabel('classifers')\n",
    "plt.ylabel('accuracy')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---------------------------------------------------------\n",
      "estimator : Pipeline(steps=[('scaler1', StandardScaler()),\n",
      "                ('dt_classifier', DecisionTreeClassifier())])\n",
      "\n",
      "classification Report: \n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.98      0.98      0.98        43\n",
      "           1       0.86      0.82      0.84        44\n",
      "           2       0.85      0.83      0.84        41\n",
      "           3       0.88      0.88      0.88        34\n",
      "           4       0.95      0.85      0.90        41\n",
      "           5       0.96      0.87      0.92        31\n",
      "           6       0.93      0.87      0.90        30\n",
      "           7       0.79      0.93      0.85        28\n",
      "           8       0.65      0.80      0.72        35\n",
      "           9       0.81      0.79      0.80        33\n",
      "\n",
      "    accuracy                           0.86       360\n",
      "   macro avg       0.87      0.86      0.86       360\n",
      "weighted avg       0.87      0.86      0.86       360\n",
      "\n",
      "\n",
      "---------------------------------------------------------\n",
      "estimator : Pipeline(steps=[('scaler2', StandardScaler()),\n",
      "                ('rf_classifier', RandomForestClassifier())])\n",
      "\n",
      "classification Report: \n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.98      1.00      0.99        42\n",
      "           1       1.00      0.93      0.97        45\n",
      "           2       1.00      1.00      1.00        40\n",
      "           3       1.00      0.97      0.99        35\n",
      "           4       0.97      0.88      0.92        41\n",
      "           5       1.00      0.90      0.95        31\n",
      "           6       0.96      1.00      0.98        27\n",
      "           7       0.94      0.97      0.95        32\n",
      "           8       0.84      1.00      0.91        36\n",
      "           9       0.94      0.97      0.95        31\n",
      "\n",
      "    accuracy                           0.96       360\n",
      "   macro avg       0.96      0.96      0.96       360\n",
      "weighted avg       0.96      0.96      0.96       360\n",
      "\n",
      "\n",
      "---------------------------------------------------------\n",
      "estimator : Pipeline(steps=[('scaler3', StandardScaler()), ('svm_classifier', SVC())])\n",
      "\n",
      "classification Report: \n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      1.00      1.00        43\n",
      "           1       1.00      0.98      0.99        43\n",
      "           2       1.00      1.00      1.00        40\n",
      "           3       1.00      1.00      1.00        34\n",
      "           4       1.00      1.00      1.00        37\n",
      "           5       1.00      0.97      0.98        29\n",
      "           6       1.00      1.00      1.00        28\n",
      "           7       1.00      1.00      1.00        33\n",
      "           8       0.98      1.00      0.99        42\n",
      "           9       0.97      1.00      0.98        31\n",
      "\n",
      "    accuracy                           0.99       360\n",
      "   macro avg       0.99      0.99      0.99       360\n",
      "weighted avg       0.99      0.99      0.99       360\n",
      "\n",
      "\n",
      "---------------------------------------------------------\n",
      "estimator : Pipeline(steps=[('scaler4', StandardScaler()),\n",
      "                ('sgd_classifier', SGDClassifier())])\n",
      "\n",
      "classification Report: \n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      1.00      1.00        43\n",
      "           1       0.86      0.95      0.90        38\n",
      "           2       0.97      0.97      0.97        40\n",
      "           3       0.91      0.86      0.89        36\n",
      "           4       0.95      1.00      0.97        35\n",
      "           5       1.00      0.90      0.95        31\n",
      "           6       0.93      0.96      0.95        27\n",
      "           7       0.97      0.97      0.97        33\n",
      "           8       0.93      0.87      0.90        46\n",
      "           9       0.88      0.90      0.89        31\n",
      "\n",
      "    accuracy                           0.94       360\n",
      "   macro avg       0.94      0.94      0.94       360\n",
      "weighted avg       0.94      0.94      0.94       360\n",
      "\n",
      "\n",
      "---------------------------------------------------------\n",
      "estimator : Pipeline(steps=[('scaler5', StandardScaler()),\n",
      "                ('lr_classifier', LogisticRegression())])\n",
      "\n",
      "classification Report: \n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      1.00      1.00        43\n",
      "           1       0.93      0.93      0.93        42\n",
      "           2       1.00      0.98      0.99        41\n",
      "           3       1.00      0.97      0.99        35\n",
      "           4       0.97      1.00      0.99        36\n",
      "           5       1.00      0.88      0.93        32\n",
      "           6       0.93      1.00      0.96        26\n",
      "           7       1.00      1.00      1.00        33\n",
      "           8       0.88      0.95      0.92        40\n",
      "           9       0.91      0.91      0.91        32\n",
      "\n",
      "    accuracy                           0.96       360\n",
      "   macro avg       0.96      0.96      0.96       360\n",
      "weighted avg       0.96      0.96      0.96       360\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "cm_list = [] \n",
    "\n",
    "for pipe in pipelines:\n",
    "    print(\"---------------------------------------------------------\")    \n",
    "    y_pred = pipe.predict(X_test)\n",
    "    cm = confusion_matrix(y_test, y_pred)\n",
    "    cm_list.append(cm)\n",
    "    print('estimator : {}\\n'.format(pipe))\n",
    "    print(\"classification Report: \\n{}\\n\".format(classification_report(y_pred, y_test)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_confusion_matrix(cm_list,model_list, i, j):\n",
    "    idx = 1\n",
    "    for cm, model in zip(cm_list,model_list):\n",
    "        if idx <= (i * j):\n",
    "            plt.figure(figsize=(15,15))\n",
    "            plt.subplot(i, j, idx)\n",
    "            cm_matrix = pd.DataFrame(data=cm)\n",
    "            sns.heatmap(cm_matrix, annot=True, fmt='d', cmap='Greens').set_title('Confusion Matrix of {}'.format(model))\n",
    "        else:\n",
    "            break\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_confusion_matrix(cm_list,model_list, 5, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "results = {\n",
    "    'Accuracy Scores of Models' : test_scores\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "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>Accuracy Scores of Models</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DecisionTree</th>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RandomForest</th>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SVM</th>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SGD</th>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Logistic Regression</th>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Accuracy Scores of Models\n",
       "DecisionTree                                70\n",
       "RandomForest                                92\n",
       "SVM                                         95\n",
       "SGD                                         92\n",
       "Logistic Regression                         94"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_df = pd.DataFrame(results, index=model_list)\n",
    "results_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  어떤 평가 기준을 선택해야할까?\n",
    "```\n",
    "숫자 분류에서는 여러가지 모델의 성능 지표 중 accuracy를 사용한다. \n",
    "다른 예제들 처럼 recall 혹은 precision을 반드시 고려해야 하는 문제가 아니기 때문이다.\n",
    "그래서 5개 모델 중에 accuracy가 가장 높은 SVM 분류기를 사용하면 좋을 것 같다.\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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