Sklearn SVM

1 개요

Sklearn SVM

2 예시 1

• 랜덤 6:4 데이터 분할 - SVM모델 훈련 - 정확도 확인

Python

CPU

1.2s

MEM

77M

1.5s

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from sklearn.model_selection import train_test_split
from sklearn import datasets
from sklearn import svm

X, y = datasets.load_iris(return_X_y=True)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=0)
clf = svm.SVC(kernel='linear', C=1).fit(X_train, y_train)
score = clf.score(X_test, y_test)
print( score )

0.9666666666666667

3 같이 보기

• SVM

4 참고

• https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html
• https://scikit-learn.org/stable/modules/cross_validation.html#computing-cross-validated-metrics