classifer = clf()
classifer.fit(x_train, y_train)
predict = sklearn.model_selection.cross_val_predict(classifer, x_test, y_test, cv=10)

scores = sklearn.model_selection.cross_val_score(classifer, x_test, y_test, cv=10)
print (scores)
print ("Accurecy of %s: %0.2f (+/- %0.2f)" % (classifer, scores.mean(), scores.std() *2))
print (classification_report(y_test, predict))