Evaluate the SGB regressor

You have prepared the ground to determine the test set RMSE of sgbr which you shall evaluate in this exercise.

y_pred and y_test are available in your workspace.

This exercise is part of the course

Machine Learning with Tree-Based Models in Python

Exercise instructions

Import mean_squared_error as MSE from sklearn.metrics.
Compute test set MSE and assign the result to mse_test.
Compute test set RMSE and assign the result to rmse_test.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import mean_squared_error as MSE
____

# Compute test set MSE
mse_test = ____

# Compute test set RMSE
rmse_test = ____

# Print rmse_test
print('Test set RMSE of sgbr: {:.3f}'.format(rmse_test))

Edit and Run Code

This exercise is part of the course

Machine Learning with Tree-Based Models in Python

IntermediateSkill Level

4.9+

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Exercise 1: Bagging Exercise 2: Define the bagging classifier Exercise 3: Evaluate Bagging performance Exercise 4: Out of Bag Evaluation Exercise 5: Prepare the ground Exercise 6: OOB Score vs Test Set Score Exercise 7: Random Forests (RF)Exercise 8: Train an RF regressor Exercise 9: Evaluate the RF regressor Exercise 10: Visualizing features importances

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Exercise 1: Adaboost Exercise 2: Define the AdaBoost classifier Exercise 3: Train the AdaBoost classifier Exercise 4: Evaluate the AdaBoost classifier Exercise 5: Gradient Boosting (GB)Exercise 6: Define the GB regressor Exercise 7: Train the GB regressor Exercise 8: Evaluate the GB regressor Exercise 9: Stochastic Gradient Boosting (SGB)Exercise 10: Regression with SGB Exercise 11: Train the SGB regressor Exercise 12: Evaluate the SGB regressor

Current Exercise

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Exercise 1: Tuning a CART's Hyperparameters Exercise 2: Tree hyperparameters Exercise 3: Set the tree's hyperparameter grid Exercise 4: Search for the optimal tree Exercise 5: Evaluate the optimal tree Exercise 6: Tuning a RF's Hyperparameters Exercise 7: Random forests hyperparameters Exercise 8: Set the hyperparameter grid of RF Exercise 9: Search for the optimal forest Exercise 10: Evaluate the optimal forest Exercise 11: Congratulations!