Example to use stack_model.py

stack_model_example.py

from sklearn.ensemble import RandomForestRegressor, GradientBoostingRegressor
from sklearn.linear_model import ElasticNet
from stack_model import stack_model

rf_model = RandomForestRegressor()
gbm_model = GradientBoostingRegressor()
en_model = ElasticNet()

base_models = [rf_model,gbm_model,en_model]
meta_model = RandomForestRegressor(n_estimators =100)
stk_model = stack_model(base_models,meta_model,X[selected_features],y.values)
stk_model.fit(cvFolds = 5, random_state= 42)