X_train, X_test, y_train, y_test = split_data(X,y)

classlist = [LDA(), SVC(kernel='linear'), SVC(kernel='rbf'), logreg(), randfor(n_estimators=100)]
scorelist = []

for el in classlist:
    classifier = el
    print(X_train.shape)
    classifier.fit(X_train, y_train)
    y_pred = classifier.predict(X_test)
    score = accuracy_score(y_test, y_pred)
    scorelist.append(score)