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#DECISION TREES
# Define model
decisionTrees_model = DecisionTreeRegressor()
# Fit model
decisionTrees_model.fit(train_X, train_Y)
#Get predicted prices on validation data and print MAE
print("Mean Absolute Error:","\n")
print(mean_absolute_error(test_Y, melbourne_model.predict(test_X)))


#RANDOM FOREST
# Define model
randomForest_model = RandomForestRegressor()
# Fit model
randomForest_model.fit(train_X, train_Y)
#Get predicted prices on validation data and print MAE
print("Mean Absolute Error:","\n")
print(mean_absolute_error(test_Y, melbourne_model.predict(test_X)))