doc.py 文件源码

def crossValidation(clf, X, Y, num=None):
    '''
        num: can be number of trees or nearest neighbours
    '''
    scores = []
    cv = StratifiedKFold(Y, n_folds=5)
    for train, test in cv:
        X_train, y_train = X[train], Y[train]
        X_test, y_test = X[test], Y[test]
        clf.fit( X_train, y_train )
        scores.append(clf.score( X_test, y_test ))
    if num:
        print("Classifier: " + str (clf.__str__ )+ "\t Mean(scores)= " + str (np.mean(scores) ) + "\tStddev(scores)= " + str (np.std(scores))+ "\t Number of neighbours / trees= " + str (num) + "\n")
        logFile ("Classifier: " + str (clf.__str__ )+ "\t Mean(scores)= " + str (np.mean(scores) ) + "\tStddev(scores)= " + str (np.std(scores))+ "\t Number of neighbours / trees= " + str (num) + "\n")
    else:
        print("Classifier: " + str (clf.__str__ )+ "\t Mean(scores)= " + str (np.mean(scores) ) + "\tStddev(scores)= " + str (np.std(scores)) + "\n")
        logFile ("Classifier: " + str (clf.__str__ )+ "\t Mean(scores)= " + str (np.mean(scores) ) + "\tStddev(scores)= " + str (np.std(scores)) + "\n")