ens_weightedavg.py

#fit base models
linear_reg.fit(X_train, y_train)
knn_reg.fit(X_train, y_train)
svr_reg.fit(X_train, y_train)

#make predictions with trained models
pred1 = linear_reg.predict(X_val)
pred2 = knn_reg.predict(X_val)
pred3 = svr_reg.predict(X_val)

#Take average as final prediction
w_avgpred = (0.5 * pred1 + 0.25 * pred2 + 0.25* pred3)

print("Linear Regression Model")
print(get_mae(pred1, y_val))
print("KNN Regression Model")
print(get_mae(pred2, y_val))
print("SVR Regression Model")
print(get_mae(pred3, y_val))
print("Weighted Average Model")
print(get_mae(w_avgpred, y_val))