train.py 文件源码

def grid_search_cv(clf, x, y, params, cv = 5):
    """
    :param clf: The classifier over which we want to perform 
    gridsearch.
    :param x: Features 
    :param y: Target
    :param params: Hyperparameters to perform gs on
    :cv: kfold cv parameter
    """
    gs = GridSearchCV(clf, param_grid = params, cv = cv)
    gs.fit(x, y)
    print 
    print 'BEST PARAMS:', gs.best_params_
    print 'BEST SCORE:', gs.best_score_
    print 
    best_estimator = gs.best_estimator_
    return best_estimator

######################
# PREPARING THE DATA #
######################

#get the last 4 images from each file