image-classification.py 文件源码

def accuracy(features, labels):
    from sklearn.linear_model import LogisticRegression
    from sklearn.pipeline import Pipeline
    from sklearn.preprocessing import StandardScaler
    from sklearn import cross_validation
    # We use logistic regression because it is very fast.
    # Feel free to experiment with other classifiers
    clf = Pipeline([('preproc', StandardScaler()),
                ('classifier', LogisticRegression())])
    cv = cross_validation.LeaveOneOut(len(features))
    scores = cross_validation.cross_val_score(
        clf, features, labels, cv=cv)
    return scores.mean()