KFold Example

from sklearn.tree import DecisionTreeClassifier

from sklearn.model_selection import StratifiedKFold, KFold

from sklearn.metrics import accuracy_score, f1_score

kfold = StratifiedKFold(n_splits=6)

X = all_chevorlet.drop(["Label"], axis=1)

y = all_chevorlet["Label"]

decisionTree_accuracy = []

temp = []

try:

    for train_index, test_index in kfold.split(X, y):

    #     print(train_index, test_index)

        dc_clf = DecisionTreeClassifier()

        X_train = X.iloc[train_index].values

        y_train = y.iloc[train_index].values

        X_test = X.iloc[test_index].values

        y_test = y.iloc[test_index].values

        dc_clf.fit( X_train, y_train )

        y_pred = dc_clf.predict( X_test )

        decisionTree_accuracy.append(accuracy_score(y_pred, y_test))

        print('accuracy: ', decisionTree_accuracy[-1])

        print('f1_score: ', f1_score(y_pred, y_test))

except Exception as e:

    print(e)

    temp = train_index