常見的集成學習有Voting、Bagging、Boost和Stacking。

Voting代碼

from sklearn.model_selection import train_test_split from sklearn.datasets import make_moons from sklearn.ensemble import RandomForestClassifier from sklearn.ensemble import VotingClassifier from sklearn.linear_model import LogisticRegression from sklearn.svm import SVC# compose moon data X, y = make_moons(n_samples=500, noise=0.30, random_state=42) X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)log_clf = LogisticRegression() rnd_clf = RandomForestClassifier() svm_clf = SVC()voting_clf = VotingClassifier(estimators=[('lr', log_clf), ('rf', rnd_clf), ('svc', svm_clf)],voting='hard' )voting_clf.fit(X_train, y_train)from sklearn.metrics import accuracy_scorefor clf in (log_clf, rnd_clf, svm_clf, voting_clf):clf.fit(X_train, y_train)y_pred = clf.predict(X_test) print(clf.__class__.__name__, accuracy_score(y_test, y_pred))

總結

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