2191 lines
515 KiB
Plaintext
2191 lines
515 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"CPython 3.5.5\n",
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"IPython 6.2.1\n",
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"\n",
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"numpy 1.14.1\n",
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"scipy 1.0.0\n",
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"sklearn 0.19.1\n",
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"pandas 0.22.0\n",
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"matplotlib 2.2.2\n"
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]
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}
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],
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"source": [
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"%load_ext watermark\n",
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"%watermark -v -p numpy,scipy,sklearn,pandas,matplotlib"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**7장 – 앙상블 학습과 랜덤 포레스트**"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"_이 노트북은 7장에 있는 모든 샘플 코드와 연습문제 해답을 가지고 있습니다._\n",
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"\n",
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"-여기에서 발생하는 경고는 NumPy에 관련된 것([#10449](https://github.com/scikit-learn/scikit-learn/issues/10449))으로 향후 버전에서는 사라질 것입니다._"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# 설정"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"파이썬 2와 3을 모두 지원합니다. 공통 모듈을 임포트하고 맷플롯립 그림이 노트북 안에 포함되도록 설정하고 생성한 그림을 저장하기 위한 함수를 준비합니다:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"# 파이썬 2와 파이썬 3 지원\n",
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"from __future__ import division, print_function, unicode_literals\n",
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"\n",
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"# 공통\n",
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"import numpy as np\n",
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"import os\n",
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"\n",
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"# 일관된 출력을 위해 유사난수 초기화\n",
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"np.random.seed(42)\n",
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"\n",
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"# 맷플롯립 설정\n",
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"%matplotlib inline\n",
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"import matplotlib\n",
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"import matplotlib.pyplot as plt\n",
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"plt.rcParams['axes.labelsize'] = 14\n",
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"plt.rcParams['xtick.labelsize'] = 12\n",
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"plt.rcParams['ytick.labelsize'] = 12\n",
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"\n",
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"# 한글출력\n",
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"plt.rcParams['font.family'] = 'NanumBarunGothic'\n",
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"plt.rcParams['axes.unicode_minus'] = False\n",
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"\n",
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"# 그림을 저장할 폴더\n",
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"PROJECT_ROOT_DIR = \".\"\n",
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"CHAPTER_ID = \"ensembles\"\n",
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"\n",
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"def image_path(fig_id):\n",
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" return os.path.join(PROJECT_ROOT_DIR, \"images\", CHAPTER_ID, fig_id)\n",
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"\n",
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"def save_fig(fig_id, tight_layout=True):\n",
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" if tight_layout:\n",
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" plt.tight_layout()\n",
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" plt.savefig(image_path(fig_id) + \".png\", format='png', dpi=300)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# 투표기반 분류기"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"heads_proba = 0.51\n",
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"coin_tosses = (np.random.rand(10000, 10) < heads_proba).astype(np.int32)\n",
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"cumulative_heads_ratio = np.cumsum(coin_tosses, axis=0) / np.arange(1, 10001).reshape(-1, 1)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 576x252 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.figure(figsize=(8,3.5))\n",
|
||
"plt.plot(cumulative_heads_ratio)\n",
|
||
"plt.plot([0, 10000], [0.51, 0.51], \"k--\", linewidth=2, label=\"51%\")\n",
|
||
"plt.plot([0, 10000], [0.5, 0.5], \"k-\", label=\"50%\")\n",
|
||
"plt.xlabel(\"동전을 던진 횟수\")\n",
|
||
"plt.ylabel(\"앞면이 나온 비율\")\n",
|
||
"plt.legend(loc=\"lower right\")\n",
|
||
"plt.axis([0, 10000, 0.42, 0.58])\n",
|
||
"save_fig(\"law_of_large_numbers_plot\")\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from sklearn.model_selection import train_test_split\n",
|
||
"from sklearn.datasets import make_moons\n",
|
||
"\n",
|
||
"X, y = make_moons(n_samples=500, noise=0.30, random_state=42)\n",
|
||
"X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"VotingClassifier(estimators=[('lr', LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
|
||
" intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n",
|
||
" penalty='l2', random_state=42, solver='liblinear', tol=0.0001,\n",
|
||
" verbose=0, warm_start=False)), ('rf', RandomFor...f',\n",
|
||
" max_iter=-1, probability=False, random_state=42, shrinking=True,\n",
|
||
" tol=0.001, verbose=False))],\n",
|
||
" flatten_transform=None, n_jobs=1, voting='hard', weights=None)"
|
||
]
|
||
},
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"from sklearn.ensemble import RandomForestClassifier\n",
|
||
"from sklearn.ensemble import VotingClassifier\n",
|
||
"from sklearn.linear_model import LogisticRegression\n",
|
||
"from sklearn.svm import SVC\n",
|
||
"\n",
|
||
"log_clf = LogisticRegression(random_state=42)\n",
|
||
"rnd_clf = RandomForestClassifier(random_state=42)\n",
|
||
"svm_clf = SVC(random_state=42)\n",
|
||
"\n",
|
||
"voting_clf = VotingClassifier(\n",
|
||
" estimators=[('lr', log_clf), ('rf', rnd_clf), ('svc', svm_clf)],\n",
|
||
" voting='hard')\n",
|
||
"voting_clf.fit(X_train, y_train)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# LabelEncoder 버그로 인해 생기는 DeprecationWarning 막기\n",
|
||
"# https://github.com/scikit-learn/scikit-learn/pull/9816\n",
|
||
"# https://stackoverflow.com/questions/49545947/sklearn-deprecationwarning-truth-value-of-an-array\n",
|
||
"import warnings\n",
|
||
"warnings.filterwarnings(action='ignore', category=DeprecationWarning)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"LogisticRegression 0.864\n",
|
||
"RandomForestClassifier 0.872\n",
|
||
"SVC 0.888\n",
|
||
"VotingClassifier 0.896\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/haesun/anaconda3/envs/handson-ml/lib/python3.5/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
|
||
" if diff:\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from sklearn.metrics import accuracy_score\n",
|
||
"\n",
|
||
"for clf in (log_clf, rnd_clf, svm_clf, voting_clf):\n",
|
||
" clf.fit(X_train, y_train)\n",
|
||
" y_pred = clf.predict(X_test)\n",
|
||
" print(clf.__class__.__name__, accuracy_score(y_test, y_pred))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"VotingClassifier(estimators=[('lr', LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
|
||
" intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n",
|
||
" penalty='l2', random_state=42, solver='liblinear', tol=0.0001,\n",
|
||
" verbose=0, warm_start=False)), ('rf', RandomFor...bf',\n",
|
||
" max_iter=-1, probability=True, random_state=42, shrinking=True,\n",
|
||
" tol=0.001, verbose=False))],\n",
|
||
" flatten_transform=None, n_jobs=1, voting='soft', weights=None)"
|
||
]
|
||
},
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"log_clf = LogisticRegression(random_state=42)\n",
|
||
"rnd_clf = RandomForestClassifier(random_state=42)\n",
|
||
"svm_clf = SVC(probability=True, random_state=42)\n",
|
||
"\n",
|
||
"voting_clf = VotingClassifier(\n",
|
||
" estimators=[('lr', log_clf), ('rf', rnd_clf), ('svc', svm_clf)],\n",
|
||
" voting='soft')\n",
|
||
"voting_clf.fit(X_train, y_train)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"LogisticRegression 0.864\n",
|
||
"RandomForestClassifier 0.872\n",
|
||
"SVC 0.888\n",
|
||
"VotingClassifier 0.912\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/haesun/anaconda3/envs/handson-ml/lib/python3.5/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
|
||
" if diff:\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from sklearn.metrics import accuracy_score\n",
|
||
"\n",
|
||
"for clf in (log_clf, rnd_clf, svm_clf, voting_clf):\n",
|
||
" clf.fit(X_train, y_train)\n",
|
||
" y_pred = clf.predict(X_test)\n",
|
||
" print(clf.__class__.__name__, accuracy_score(y_test, y_pred))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# 배깅 앙상블"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from sklearn.ensemble import BaggingClassifier\n",
|
||
"from sklearn.tree import DecisionTreeClassifier\n",
|
||
"\n",
|
||
"bag_clf = BaggingClassifier(\n",
|
||
" DecisionTreeClassifier(random_state=42), n_estimators=500,\n",
|
||
" max_samples=100, bootstrap=True, n_jobs=-1, random_state=42)\n",
|
||
"bag_clf.fit(X_train, y_train)\n",
|
||
"y_pred = bag_clf.predict(X_test)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"0.904\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from sklearn.metrics import accuracy_score\n",
|
||
"print(accuracy_score(y_test, y_pred))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"0.856\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"tree_clf = DecisionTreeClassifier(random_state=42)\n",
|
||
"tree_clf.fit(X_train, y_train)\n",
|
||
"y_pred_tree = tree_clf.predict(X_test)\n",
|
||
"print(accuracy_score(y_test, y_pred_tree))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from matplotlib.colors import ListedColormap\n",
|
||
"\n",
|
||
"def plot_decision_boundary(clf, X, y, axes=[-1.5, 2.5, -1, 1.5], alpha=0.5, contour=True):\n",
|
||
" x1s = np.linspace(axes[0], axes[1], 100)\n",
|
||
" x2s = np.linspace(axes[2], axes[3], 100)\n",
|
||
" x1, x2 = np.meshgrid(x1s, x2s)\n",
|
||
" X_new = np.c_[x1.ravel(), x2.ravel()]\n",
|
||
" y_pred = clf.predict(X_new).reshape(x1.shape)\n",
|
||
" custom_cmap = ListedColormap(['#fafab0','#9898ff','#a0faa0'])\n",
|
||
" plt.contourf(x1, x2, y_pred, alpha=0.3, cmap=custom_cmap)\n",
|
||
" if contour:\n",
|
||
" custom_cmap2 = ListedColormap(['#7d7d58','#4c4c7f','#507d50'])\n",
|
||
" plt.contour(x1, x2, y_pred, cmap=custom_cmap2, alpha=0.8)\n",
|
||
" plt.plot(X[:, 0][y==0], X[:, 1][y==0], \"yo\", alpha=alpha)\n",
|
||
" plt.plot(X[:, 0][y==1], X[:, 1][y==1], \"bs\", alpha=alpha)\n",
|
||
" plt.axis(axes)\n",
|
||
" plt.xlabel(r\"$x_1$\", fontsize=18)\n",
|
||
" plt.ylabel(r\"$x_2$\", fontsize=18, rotation=0)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 792x288 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.figure(figsize=(11,4))\n",
|
||
"plt.subplot(121)\n",
|
||
"plot_decision_boundary(tree_clf, X, y)\n",
|
||
"plt.title(\"결정 트리\", fontsize=14)\n",
|
||
"plt.subplot(122)\n",
|
||
"plot_decision_boundary(bag_clf, X, y)\n",
|
||
"plt.title(\"배깅을 사용한 결정 트리\", fontsize=14)\n",
|
||
"save_fig(\"decision_tree_without_and_with_bagging_plot\")\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# 랜덤 포레스트"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"bag_clf = BaggingClassifier(\n",
|
||
" DecisionTreeClassifier(splitter=\"random\", max_leaf_nodes=16, random_state=42),\n",
|
||
" n_estimators=500, max_samples=1.0, bootstrap=True, n_jobs=-1, random_state=42)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"bag_clf.fit(X_train, y_train)\n",
|
||
"y_pred = bag_clf.predict(X_test)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 17,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from sklearn.ensemble import RandomForestClassifier\n",
|
||
"\n",
|
||
"rnd_clf = RandomForestClassifier(n_estimators=500, max_leaf_nodes=16, n_jobs=-1, random_state=42)\n",
|
||
"rnd_clf.fit(X_train, y_train)\n",
|
||
"\n",
|
||
"y_pred_rf = rnd_clf.predict(X_test)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"0.976"
|
||
]
|
||
},
|
||
"execution_count": 18,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"np.sum(y_pred == y_pred_rf) / len(y_pred) # 거의 동일한 예측"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 19,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"sepal length (cm) 0.11249225099876374\n",
|
||
"sepal width (cm) 0.023119288282510326\n",
|
||
"petal length (cm) 0.44103046436395765\n",
|
||
"petal width (cm) 0.4233579963547681\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from sklearn.datasets import load_iris\n",
|
||
"iris = load_iris()\n",
|
||
"rnd_clf = RandomForestClassifier(n_estimators=500, n_jobs=-1, random_state=42)\n",
|
||
"rnd_clf.fit(iris[\"data\"], iris[\"target\"])\n",
|
||
"for name, score in zip(iris[\"feature_names\"], rnd_clf.feature_importances_):\n",
|
||
" print(name, score)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 20,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"array([0.11249225, 0.02311929, 0.44103046, 0.423358 ])"
|
||
]
|
||
},
|
||
"execution_count": 20,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"rnd_clf.feature_importances_"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 21,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.figure(figsize=(6, 4))\n",
|
||
"\n",
|
||
"for i in range(15):\n",
|
||
" tree_clf = DecisionTreeClassifier(max_leaf_nodes=16, random_state=42 + i)\n",
|
||
" indices_with_replacement = np.random.randint(0, len(X_train), len(X_train))\n",
|
||
" tree_clf.fit(X[indices_with_replacement], y[indices_with_replacement])\n",
|
||
" plot_decision_boundary(tree_clf, X, y, axes=[-1.5, 2.5, -1, 1.5], alpha=0.02, contour=False)\n",
|
||
"\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## oob 평가"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"0.9013333333333333"
|
||
]
|
||
},
|
||
"execution_count": 22,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"bag_clf = BaggingClassifier(\n",
|
||
" DecisionTreeClassifier(random_state=42), n_estimators=500,\n",
|
||
" bootstrap=True, n_jobs=-1, oob_score=True, random_state=40)\n",
|
||
"bag_clf.fit(X_train, y_train)\n",
|
||
"bag_clf.oob_score_"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 23,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"array([[0.31746032, 0.68253968],\n",
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||
" [0.34117647, 0.65882353],\n",
|
||
" [1. , 0. ],\n",
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||
" [0. , 1. ],\n",
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||
" [0. , 1. ],\n",
|
||
" [0.08379888, 0.91620112],\n",
|
||
" [0.31693989, 0.68306011],\n",
|
||
" [0.02923977, 0.97076023],\n",
|
||
" [0.97687861, 0.02312139],\n",
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||
" [0.97765363, 0.02234637],\n",
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||
" [0.74404762, 0.25595238],\n",
|
||
" [0. , 1. ],\n",
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" [0.71195652, 0.28804348],\n",
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" [0.83957219, 0.16042781],\n",
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" [0.97777778, 0.02222222],\n",
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" [0.0625 , 0.9375 ],\n",
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" [0. , 1. ],\n",
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" [0.97297297, 0.02702703],\n",
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" [0.95238095, 0.04761905],\n",
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" [1. , 0. ],\n",
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" [0.01704545, 0.98295455],\n",
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" [0.38947368, 0.61052632],\n",
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" [0.88700565, 0.11299435],\n",
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" [1. , 0. ],\n",
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" [0.96685083, 0.03314917],\n",
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" [0. , 1. ],\n",
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" [0. , 1. ],\n",
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" [0.13402062, 0.86597938],\n",
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" [1. , 0. ],\n",
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" [0. , 1. ],\n",
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" [0.36065574, 0.63934426],\n",
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" [1. , 0. ],\n",
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" [0.27093596, 0.72906404],\n",
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" [0.34146341, 0.65853659],\n",
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" [1. , 0. ],\n",
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" [0. , 1. ],\n",
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" [1. , 0. ],\n",
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" [0. , 1. ],\n",
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" [1. , 0. ],\n",
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" [0.00531915, 0.99468085],\n",
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" [0.91428571, 0.08571429],\n",
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" [0.97282609, 0.02717391],\n",
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" [0.97029703, 0.02970297],\n",
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" [0. , 1. ],\n",
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" [0.06134969, 0.93865031],\n",
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" [0. , 1. ],\n",
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" [0. , 1. ],\n",
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" [0.97790055, 0.02209945],\n",
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" [0.87356322, 0.12643678],\n",
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" [1. , 0. ],\n",
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" [0.56140351, 0.43859649],\n",
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" [0.16304348, 0.83695652],\n",
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" [0.67539267, 0.32460733],\n",
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" [0.90673575, 0.09326425],\n",
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" [0. , 1. ],\n",
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" [0.16201117, 0.83798883],\n",
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" [0.05418719, 0.94581281],\n",
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" [0.29533679, 0.70466321],\n",
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" [1. , 0. ],\n",
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" [0. , 1. ],\n",
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" [0.81871345, 0.18128655],\n",
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" [0. , 1. ],\n",
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|
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" [0.57291667, 0.42708333]])"
|
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]
|
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},
|
||
"execution_count": 23,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"bag_clf.oob_decision_function_"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"0.912"
|
||
]
|
||
},
|
||
"execution_count": 24,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"from sklearn.metrics import accuracy_score\n",
|
||
"y_pred = bag_clf.predict(X_test)\n",
|
||
"accuracy_score(y_test, y_pred)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 특성 중요도"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 25,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from sklearn.datasets import fetch_mldata\n",
|
||
"mnist = fetch_mldata('MNIST original')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 26,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n",
|
||
" max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
|
||
" min_impurity_decrease=0.0, min_impurity_split=None,\n",
|
||
" min_samples_leaf=1, min_samples_split=2,\n",
|
||
" min_weight_fraction_leaf=0.0, n_estimators=10, n_jobs=1,\n",
|
||
" oob_score=False, random_state=42, verbose=0, warm_start=False)"
|
||
]
|
||
},
|
||
"execution_count": 26,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"rnd_clf = RandomForestClassifier(random_state=42)\n",
|
||
"rnd_clf.fit(mnist[\"data\"], mnist[\"target\"])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 27,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"def plot_digit(data):\n",
|
||
" image = data.reshape(28, 28)\n",
|
||
" plt.imshow(image, cmap = matplotlib.cm.hot,\n",
|
||
" interpolation=\"nearest\")\n",
|
||
" plt.axis(\"off\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 28,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plot_digit(rnd_clf.feature_importances_)\n",
|
||
"\n",
|
||
"cbar = plt.colorbar(ticks=[rnd_clf.feature_importances_.min(), rnd_clf.feature_importances_.max()])\n",
|
||
"cbar.ax.set_yticklabels(['중요하지 않음', '매우 중요함'])\n",
|
||
"\n",
|
||
"save_fig(\"mnist_feature_importance_plot\")\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# 아다부스트"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 29,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"AdaBoostClassifier(algorithm='SAMME.R',\n",
|
||
" base_estimator=DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=1,\n",
|
||
" max_features=None, max_leaf_nodes=None,\n",
|
||
" min_impurity_decrease=0.0, min_impurity_split=None,\n",
|
||
" min_samples_leaf=1, min_samples_split=2,\n",
|
||
" min_weight_fraction_leaf=0.0, presort=False, random_state=None,\n",
|
||
" splitter='best'),\n",
|
||
" learning_rate=0.5, n_estimators=200, random_state=42)"
|
||
]
|
||
},
|
||
"execution_count": 29,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"from sklearn.ensemble import AdaBoostClassifier\n",
|
||
"\n",
|
||
"ada_clf = AdaBoostClassifier(\n",
|
||
" DecisionTreeClassifier(max_depth=1), n_estimators=200,\n",
|
||
" algorithm=\"SAMME.R\", learning_rate=0.5, random_state=42)\n",
|
||
"ada_clf.fit(X_train, y_train)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 30,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plot_decision_boundary(ada_clf, X, y)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 31,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 792x288 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"m = len(X_train)\n",
|
||
"\n",
|
||
"plt.figure(figsize=(11, 4))\n",
|
||
"for subplot, learning_rate in ((121, 1), (122, 0.5)):\n",
|
||
" sample_weights = np.ones(m)\n",
|
||
" plt.subplot(subplot)\n",
|
||
" if subplot == 121:\n",
|
||
" plt.text(-0.7, -0.65, \"1\", fontsize=14)\n",
|
||
" plt.text(-0.6, -0.10, \"2\", fontsize=14)\n",
|
||
" plt.text(-0.5, 0.10, \"3\", fontsize=14)\n",
|
||
" plt.text(-0.4, 0.55, \"4\", fontsize=14)\n",
|
||
" plt.text(-0.3, 0.90, \"5\", fontsize=14) \n",
|
||
" for i in range(5):\n",
|
||
" svm_clf = SVC(kernel=\"rbf\", C=0.05, random_state=42)\n",
|
||
" svm_clf.fit(X_train, y_train, sample_weight=sample_weights)\n",
|
||
" y_pred = svm_clf.predict(X_train)\n",
|
||
" sample_weights[y_pred != y_train] *= (1 + learning_rate)\n",
|
||
" plot_decision_boundary(svm_clf, X, y, alpha=0.2)\n",
|
||
" plt.title(\"learning_rate = {}\".format(learning_rate), fontsize=16)\n",
|
||
"\n",
|
||
"save_fig(\"boosting_plot\")\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 32,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"['base_estimator_',\n",
|
||
" 'classes_',\n",
|
||
" 'estimator_errors_',\n",
|
||
" 'estimator_weights_',\n",
|
||
" 'estimators_',\n",
|
||
" 'feature_importances_',\n",
|
||
" 'n_classes_']"
|
||
]
|
||
},
|
||
"execution_count": 32,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"list(m for m in dir(ada_clf) if not m.startswith(\"_\") and m.endswith(\"_\"))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# 그래디언트 부스팅"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 33,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"np.random.seed(42)\n",
|
||
"X = np.random.rand(100, 1) - 0.5\n",
|
||
"y = 3*X[:, 0]**2 + 0.05 * np.random.randn(100)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 34,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"DecisionTreeRegressor(criterion='mse', max_depth=2, max_features=None,\n",
|
||
" max_leaf_nodes=None, min_impurity_decrease=0.0,\n",
|
||
" min_impurity_split=None, min_samples_leaf=1,\n",
|
||
" min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
|
||
" presort=False, random_state=42, splitter='best')"
|
||
]
|
||
},
|
||
"execution_count": 34,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"from sklearn.tree import DecisionTreeRegressor\n",
|
||
"\n",
|
||
"tree_reg1 = DecisionTreeRegressor(max_depth=2, random_state=42)\n",
|
||
"tree_reg1.fit(X, y)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 35,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"DecisionTreeRegressor(criterion='mse', max_depth=2, max_features=None,\n",
|
||
" max_leaf_nodes=None, min_impurity_decrease=0.0,\n",
|
||
" min_impurity_split=None, min_samples_leaf=1,\n",
|
||
" min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
|
||
" presort=False, random_state=42, splitter='best')"
|
||
]
|
||
},
|
||
"execution_count": 35,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"y2 = y - tree_reg1.predict(X)\n",
|
||
"tree_reg2 = DecisionTreeRegressor(max_depth=2, random_state=42)\n",
|
||
"tree_reg2.fit(X, y2)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 36,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"DecisionTreeRegressor(criterion='mse', max_depth=2, max_features=None,\n",
|
||
" max_leaf_nodes=None, min_impurity_decrease=0.0,\n",
|
||
" min_impurity_split=None, min_samples_leaf=1,\n",
|
||
" min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
|
||
" presort=False, random_state=42, splitter='best')"
|
||
]
|
||
},
|
||
"execution_count": 36,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"y3 = y2 - tree_reg2.predict(X)\n",
|
||
"tree_reg3 = DecisionTreeRegressor(max_depth=2, random_state=42)\n",
|
||
"tree_reg3.fit(X, y3)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 37,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"X_new = np.array([[0.8]])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 38,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"y_pred = sum(tree.predict(X_new) for tree in (tree_reg1, tree_reg2, tree_reg3))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 39,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"array([0.75026781])"
|
||
]
|
||
},
|
||
"execution_count": 39,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"y_pred"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 40,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 792x792 with 6 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"def plot_predictions(regressors, X, y, axes, label=None, style=\"r-\", data_style=\"b.\", data_label=None):\n",
|
||
" x1 = np.linspace(axes[0], axes[1], 500)\n",
|
||
" y_pred = sum(regressor.predict(x1.reshape(-1, 1)) for regressor in regressors)\n",
|
||
" plt.plot(X[:, 0], y, data_style, label=data_label)\n",
|
||
" plt.plot(x1, y_pred, style, linewidth=2, label=label)\n",
|
||
" if label or data_label:\n",
|
||
" plt.legend(loc=\"upper center\", fontsize=16)\n",
|
||
" plt.axis(axes)\n",
|
||
"\n",
|
||
"plt.figure(figsize=(11,11))\n",
|
||
"\n",
|
||
"plt.subplot(321)\n",
|
||
"plot_predictions([tree_reg1], X, y, axes=[-0.5, 0.5, -0.1, 0.8], label=\"$h_1(x_1)$\", style=\"g-\", data_label=\"훈련 세트\")\n",
|
||
"plt.ylabel(\"$y$\", fontsize=16, rotation=0)\n",
|
||
"plt.title(\"잔여 오차와 트리의 예측\", fontsize=16)\n",
|
||
"\n",
|
||
"plt.subplot(322)\n",
|
||
"plot_predictions([tree_reg1], X, y, axes=[-0.5, 0.5, -0.1, 0.8], label=\"$h(x_1) = h_1(x_1)$\", data_label=\"훈련 세트\")\n",
|
||
"plt.ylabel(\"$y$\", fontsize=16, rotation=0)\n",
|
||
"plt.title(\"앙상블의 예측\", fontsize=16)\n",
|
||
"\n",
|
||
"plt.subplot(323)\n",
|
||
"plot_predictions([tree_reg2], X, y2, axes=[-0.5, 0.5, -0.5, 0.5], label=\"$h_2(x_1)$\", style=\"g-\", data_style=\"k+\", data_label=\"잔여 오차\")\n",
|
||
"plt.ylabel(\"$y - h_1(x_1)$\", fontsize=16)\n",
|
||
"\n",
|
||
"plt.subplot(324)\n",
|
||
"plot_predictions([tree_reg1, tree_reg2], X, y, axes=[-0.5, 0.5, -0.1, 0.8], label=\"$h(x_1) = h_1(x_1) + h_2(x_1)$\")\n",
|
||
"plt.ylabel(\"$y$\", fontsize=16, rotation=0)\n",
|
||
"\n",
|
||
"plt.subplot(325)\n",
|
||
"plot_predictions([tree_reg3], X, y3, axes=[-0.5, 0.5, -0.5, 0.5], label=\"$h_3(x_1)$\", style=\"g-\", data_style=\"k+\")\n",
|
||
"plt.ylabel(\"$y - h_1(x_1) - h_2(x_1)$\", fontsize=16)\n",
|
||
"plt.xlabel(\"$x_1$\", fontsize=16)\n",
|
||
"\n",
|
||
"plt.subplot(326)\n",
|
||
"plot_predictions([tree_reg1, tree_reg2, tree_reg3], X, y, axes=[-0.5, 0.5, -0.1, 0.8], label=\"$h(x_1) = h_1(x_1) + h_2(x_1) + h_3(x_1)$\")\n",
|
||
"plt.xlabel(\"$x_1$\", fontsize=16)\n",
|
||
"plt.ylabel(\"$y$\", fontsize=16, rotation=0)\n",
|
||
"\n",
|
||
"save_fig(\"gradient_boosting_plot\")\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 41,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"GradientBoostingRegressor(alpha=0.9, criterion='friedman_mse', init=None,\n",
|
||
" learning_rate=0.1, loss='ls', max_depth=2, max_features=None,\n",
|
||
" max_leaf_nodes=None, min_impurity_decrease=0.0,\n",
|
||
" min_impurity_split=None, min_samples_leaf=1,\n",
|
||
" min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
|
||
" n_estimators=3, presort='auto', random_state=42,\n",
|
||
" subsample=1.0, verbose=0, warm_start=False)"
|
||
]
|
||
},
|
||
"execution_count": 41,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"from sklearn.ensemble import GradientBoostingRegressor\n",
|
||
"\n",
|
||
"gbrt = GradientBoostingRegressor(max_depth=2, n_estimators=3, learning_rate=0.1, random_state=42)\n",
|
||
"gbrt.fit(X, y)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 42,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"GradientBoostingRegressor(alpha=0.9, criterion='friedman_mse', init=None,\n",
|
||
" learning_rate=0.1, loss='ls', max_depth=2, max_features=None,\n",
|
||
" max_leaf_nodes=None, min_impurity_decrease=0.0,\n",
|
||
" min_impurity_split=None, min_samples_leaf=1,\n",
|
||
" min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
|
||
" n_estimators=200, presort='auto', random_state=42,\n",
|
||
" subsample=1.0, verbose=0, warm_start=False)"
|
||
]
|
||
},
|
||
"execution_count": 42,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"gbrt_slow = GradientBoostingRegressor(max_depth=2, n_estimators=200, learning_rate=0.1, random_state=42)\n",
|
||
"gbrt_slow.fit(X, y)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 43,
|
||
"metadata": {
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 792x288 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.figure(figsize=(11,4))\n",
|
||
"\n",
|
||
"plt.subplot(121)\n",
|
||
"plot_predictions([gbrt], X, y, axes=[-0.5, 0.5, -0.1, 0.8], label=\"앙상블의 예측\")\n",
|
||
"plt.title(\"learning_rate={}, n_estimators={}\".format(gbrt.learning_rate, gbrt.n_estimators), fontsize=14)\n",
|
||
"\n",
|
||
"plt.subplot(122)\n",
|
||
"plot_predictions([gbrt_slow], X, y, axes=[-0.5, 0.5, -0.1, 0.8])\n",
|
||
"plt.title(\"learning_rate={}, n_estimators={}\".format(gbrt_slow.learning_rate, gbrt_slow.n_estimators), fontsize=14)\n",
|
||
"\n",
|
||
"save_fig(\"gbrt_learning_rate_plot\")\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 조기 종료를 사용한 그래디언트 부스팅"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 44,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"GradientBoostingRegressor(alpha=0.9, criterion='friedman_mse', init=None,\n",
|
||
" learning_rate=0.1, loss='ls', max_depth=2, max_features=None,\n",
|
||
" max_leaf_nodes=None, min_impurity_decrease=0.0,\n",
|
||
" min_impurity_split=None, min_samples_leaf=1,\n",
|
||
" min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
|
||
" n_estimators=55, presort='auto', random_state=42,\n",
|
||
" subsample=1.0, verbose=0, warm_start=False)"
|
||
]
|
||
},
|
||
"execution_count": 44,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"from sklearn.model_selection import train_test_split\n",
|
||
"from sklearn.metrics import mean_squared_error\n",
|
||
"\n",
|
||
"X_train, X_val, y_train, y_val = train_test_split(X, y, random_state=49)\n",
|
||
"\n",
|
||
"gbrt = GradientBoostingRegressor(max_depth=2, n_estimators=120, random_state=42)\n",
|
||
"gbrt.fit(X_train, y_train)\n",
|
||
"\n",
|
||
"errors = [mean_squared_error(y_val, y_pred)\n",
|
||
" for y_pred in gbrt.staged_predict(X_val)]\n",
|
||
"bst_n_estimators = np.argmin(errors)\n",
|
||
"\n",
|
||
"gbrt_best = GradientBoostingRegressor(max_depth=2,n_estimators=bst_n_estimators, random_state=42)\n",
|
||
"gbrt_best.fit(X_train, y_train)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 45,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"min_error = np.min(errors)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 46,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 792x288 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.figure(figsize=(11, 4))\n",
|
||
"\n",
|
||
"plt.subplot(121)\n",
|
||
"plt.plot(errors, \"b.-\")\n",
|
||
"plt.plot([bst_n_estimators, bst_n_estimators], [0, min_error], \"k--\")\n",
|
||
"plt.plot([0, 120], [min_error, min_error], \"k--\")\n",
|
||
"plt.plot(bst_n_estimators, min_error, \"ko\")\n",
|
||
"plt.text(bst_n_estimators, min_error*1.2, \"최소\", ha=\"center\", fontsize=14)\n",
|
||
"plt.axis([0, 120, 0, 0.01])\n",
|
||
"plt.xlabel(\"트리 개수\")\n",
|
||
"plt.title(\"검증 오차\", fontsize=14)\n",
|
||
"\n",
|
||
"plt.subplot(122)\n",
|
||
"plot_predictions([gbrt_best], X, y, axes=[-0.5, 0.5, -0.1, 0.8])\n",
|
||
"plt.title(\"최적 모델 (트리 %d개)\" % bst_n_estimators, fontsize=14)\n",
|
||
"\n",
|
||
"save_fig(\"early_stopping_gbrt_plot\")\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 47,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"gbrt = GradientBoostingRegressor(max_depth=2, warm_start=True, random_state=42)\n",
|
||
"\n",
|
||
"min_val_error = float(\"inf\")\n",
|
||
"error_going_up = 0\n",
|
||
"for n_estimators in range(1, 120):\n",
|
||
" gbrt.n_estimators = n_estimators\n",
|
||
" gbrt.fit(X_train, y_train)\n",
|
||
" y_pred = gbrt.predict(X_val)\n",
|
||
" val_error = mean_squared_error(y_val, y_pred)\n",
|
||
" if val_error < min_val_error:\n",
|
||
" min_val_error = val_error\n",
|
||
" error_going_up = 0\n",
|
||
" else:\n",
|
||
" error_going_up += 1\n",
|
||
" if error_going_up == 5:\n",
|
||
" break # 조기 종료"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 48,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"61\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(gbrt.n_estimators)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"print(\"최소 검증 MSE:\", min_val_error)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# XGBoost"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"try:\n",
|
||
" import xgboost\n",
|
||
"except ImportError as ex:\n",
|
||
" print(\"에러: xgboost 라이브러리가 설치되지 않았습니다.\")\n",
|
||
" xgboost = None"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"if xgboost is not None: # 책에는 없음\n",
|
||
" xgb_reg = xgboost.XGBRegressor(random_state=42)\n",
|
||
" xgb_reg.fit(X_train, y_train)\n",
|
||
" y_pred = xgb_reg.predict(X_val)\n",
|
||
" val_error = mean_squared_error(y_val, y_pred)\n",
|
||
" print(\"검증 MSE:\", val_error)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"if xgboost is not None: # 책에는 없음\n",
|
||
" xgb_reg.fit(X_train, y_train,\n",
|
||
" eval_set=[(X_val, y_val)], early_stopping_rounds=2)\n",
|
||
" y_pred = xgb_reg.predict(X_val)\n",
|
||
" val_error = mean_squared_error(y_val, y_pred)\n",
|
||
" print(\"검증 MSE:\", val_error)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"%timeit xgboost.XGBRegressor().fit(X_train, y_train) if xgboost is not None else None"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"%timeit GradientBoostingRegressor().fit(X_train, y_train)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {
|
||
"collapsed": true
|
||
},
|
||
"source": [
|
||
"# 연습문제 해답"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 1. to 7.\n",
|
||
"\n",
|
||
"부록 A를 참조."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 8. 투표 기반 분류기\n",
|
||
"\n",
|
||
"*문제: MNIST 데이터를 불러들여 훈련 세트, 검증 세트, 테스트 세트로 나눕니다(예를 들면 훈련에 40,000개 샘플, 검증에 10,000개 샘플, 테스트에 10,000개 샘플).*"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from sklearn.datasets import fetch_mldata"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"mnist = fetch_mldata('MNIST original')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from sklearn.model_selection import train_test_split"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"X_train_val, X_test, y_train_val, y_test = train_test_split(\n",
|
||
" mnist.data, mnist.target, test_size=10000, random_state=42)\n",
|
||
"X_train, X_val, y_train, y_val = train_test_split(\n",
|
||
" X_train_val, y_train_val, test_size=10000, random_state=42)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"*문제: 그런 다음 랜덤 포레스트 분류기, 엑스트라 트리 분류기, SVM 같은 여러 종류의 분류기를 훈련시킵니다.*"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from sklearn.ensemble import RandomForestClassifier, ExtraTreesClassifier\n",
|
||
"from sklearn.svm import LinearSVC\n",
|
||
"from sklearn.neural_network import MLPClassifier"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"random_forest_clf = RandomForestClassifier(random_state=42)\n",
|
||
"extra_trees_clf = ExtraTreesClassifier(random_state=42)\n",
|
||
"svm_clf = LinearSVC(random_state=42)\n",
|
||
"mlp_clf = MLPClassifier(random_state=42)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"estimators = [random_forest_clf, extra_trees_clf, svm_clf, mlp_clf]\n",
|
||
"for estimator in estimators:\n",
|
||
" print(\"훈련 예측기: \", estimator)\n",
|
||
" estimator.fit(X_train, y_train)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"[estimator.score(X_val, y_val) for estimator in estimators]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"선형 SVM이 다른 분류기보다 성능이 많이 떨어집니다. 그러나 투표 기반 분류기의 성능을 향상시킬 수 있으므로 그대로 두겠습니다."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"*문제: 그리고 검증 세트에서 개개의 분류기보다 더 높은 성능을 내도록 이들을 간접 또는 직접 투표 분류기를 사용하는 앙상블로 연결해보세요.*"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from sklearn.ensemble import VotingClassifier"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"named_estimators = [\n",
|
||
" (\"random_forest_clf\", random_forest_clf),\n",
|
||
" (\"extra_trees_clf\", extra_trees_clf),\n",
|
||
" (\"svm_clf\", svm_clf),\n",
|
||
" (\"mlp_clf\", mlp_clf),\n",
|
||
"]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"voting_clf = VotingClassifier(named_estimators)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"voting_clf.fit(X_train, y_train)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"voting_clf.score(X_val, y_val)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"[estimator.score(X_val, y_val) for estimator in voting_clf.estimators_]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"SVM 모델을 제거해서 성능이 향상되는지 확인해 보죠. 다음과 같이 `set_params()`를 사용하여 `None`으로 지정하면 특정 예측기를 제외시킬 수 있습니다:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"voting_clf.set_params(svm_clf=None)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"예측기 목록이 업데이트되었습니다:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"voting_clf.estimators"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"하지만 훈련된 예측기 목록은 업데이트되지 않습니다:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"voting_clf.estimators_"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"`VotingClassifier`를 다시 훈련시키거나 그냥 훈련된 예측기 목록에서 SVM 모델을 제거할 수 있습니다:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"del voting_clf.estimators_[2]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"`VotingClassifier`를 다시 평가해 보죠:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"voting_clf.score(X_val, y_val)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"훨씬 나아졌네요! SVM 모델이 성능을 저하시켰습니다. 이제 간접 투표 분류기를 사용해 보죠. 분류기를 다시 훈련시킬 필요는 없고 `voting`을 `\"soft\"`로 지정하면 됩니다:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"voting_clf.voting = \"soft\""
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"voting_clf.score(X_val, y_val)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"성능이 많이 나아졌고 개개의 분류기보다 훨씬 좋습니다."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"*문제: 앙상블을 얻고 나면 테스트 세트로 확인해보세요. 개개의 분류기와 비교해서 성능이 얼마나 향상되나요?*"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"voting_clf.score(X_test, y_test)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"[estimator.score(X_test, y_test) for estimator in voting_clf.estimators_]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"투표 기반 분류기는 에러율을 제일 좋은 모델(`MLPClassifier`)의 4.9%에서 3.5%로 줄였습니다. 약 28%나 오류가 적습니다. 나쁘지 않네요!"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 9. 스태킹 앙상블"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"*문제: 이전 연습문제의 각 분류기를 실행해서 검증 세트에서 예측을 만들고 그 결과로 새로운 훈련 세트를 만들어보세요. 각 훈련 샘플은 하나의 이미지에 대한 전체 분류기의 예측을 담은 벡터고 타깃은 이미지의 클래스입니다. 새로운 이 훈련 세트에 분류기 하나를 훈련시켜 보세요.*"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"X_val_predictions = np.empty((len(X_val), len(estimators)), dtype=np.float32)\n",
|
||
"\n",
|
||
"for index, estimator in enumerate(estimators):\n",
|
||
" X_val_predictions[:, index] = estimator.predict(X_val)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"X_val_predictions"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"rnd_forest_blender = RandomForestClassifier(n_estimators=200, oob_score=True, random_state=42)\n",
|
||
"rnd_forest_blender.fit(X_val_predictions, y_val)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"rnd_forest_blender.oob_score_"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"이 블렌더를 세밀하게 튜닝하거나 다른 종류의 블렌더(예를 들어, MLPClassifier)를 시도해 볼 수 있습니다. 그런 늘 하던대로 다음 교차 검증을 사용해 가장 좋은 것을 선택합니다."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"*문제: 축하합니다. 방금 블렌더를 훈련시켰습니다. 그리고 이 분류기를 모아서 스태킹 앙상블을 구성했습니다. 이제 테스트 세트에 앙상블을 평가해보세요. 테스트 세트의 각 이미지에 대해 모든 분류기로 예측을 만들고 앙상블의 예측 결과를 만들기 위해 블렌더에 그 예측을 주입합니다. 앞서 만든 투표 분류기와 비교하면 어떤가요?*"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"X_test_predictions = np.empty((len(X_test), len(estimators)), dtype=np.float32)\n",
|
||
"\n",
|
||
"for index, estimator in enumerate(estimators):\n",
|
||
" X_test_predictions[:, index] = estimator.predict(X_test)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"y_pred = rnd_forest_blender.predict(X_test_predictions)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from sklearn.metrics import accuracy_score"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"accuracy_score(y_test, y_pred)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"이 스태킹 앙상블은 앞서 만든 간접 투표 분류기만큼 성능을 내지는 못합니다. 하지만 개개의 분류기보다는 당연히 좋습니다."
|
||
]
|
||
}
|
||
],
|
||
"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",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.5.5"
|
||
},
|
||
"nav_menu": {
|
||
"height": "252px",
|
||
"width": "333px"
|
||
},
|
||
"toc": {
|
||
"navigate_menu": true,
|
||
"number_sections": true,
|
||
"sideBar": true,
|
||
"threshold": 6,
|
||
"toc_cell": false,
|
||
"toc_section_display": "block",
|
||
"toc_window_display": false
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 1
|
||
}
|