# initialise the base models
model_1 = tree.DecisionTreeClassifier(random_state=1)
model_2 = KNeighborsClassifier()

# train base models and create new featurs
test_pred_1 ,train_pred_1=Stacking(model=model_1,n_fold=10, train=x_train,test=x_test,y=y_train)
test_pred_2 ,train_pred_2=Stacking(model=model_2,n_fold=10,train=x_train,test=x_test,y=y_train)

# convert into dataframe for later use
train_pred_1=pd.DataFrame(train_pred_1)
test_pred_1=pd.DataFrame(test_pred_1)
train_pred_2=pd.DataFrame(train_pred_2)
test_pred_2=pd.DataFrame(test_pred_2)