optimization.py 文件源码

def random_search(clf, param_distribution, n_iter_search, X_train, y_train):
    '''
    random search with optimization without nested resampling
    @return: best_estimator, best score
    '''
    param_list = ParameterSampler(param_distribution, n_iter = n_iter_search)
    best_score = 0.0
    opt_clf = None
    for params in param_list:
        clf.set_params(**params)
        clf.fit(X_train, y_train)
        clf_accuracy = accuracy_score(y_train, clf.predict(X_train))
        if clf_accuracy > best_score:
            best_score = clf_accuracy
            opt_clf = clone(clf)

    opt_clf.fit(X_train, y_train)

    return opt_clf, best_score