train_classifiers.py 文件源码

def eval_model(clf, confusion, title, train_data, train_label, features, y):

        if (eval_all == 0):
            results = clf.fit(train_data, train_label).predict(train_data)
            cnf = confusion_matrix(train_label, results)
            print("Evaluating models on training data...")

        if (eval_all == 1):
            results = clf.fit(train_data, train_label).predict(features)
            cnf = confusion_matrix(y, results)
            #print("\n", title, clf.score(features, y),"\n",cnf)
            print("Evaluating models on training and testing data...")

        confusion.append(cnf)


    # LDA