MS-DS Master of Data science Machine Learning 5

Question 1

What is the key difference between bagging and boosting ensemble methods?

Accepted Answer

Bagging trains base learners in parallel on bootstrap samples; boosting trains them sequentially, each correcting prior errors

Answer

Bagging reduces variance by averaging independently trained models on bootstrap samples, while boosting reduces bias by sequentially fitting models that focus on previously misclassified instances.

Question 2

In a convolutional neural network (CNN), what does a pooling layer do?

Accepted Answer

Reduces spatial dimensions by aggregating features within local regions

Answer

Pooling layers (max or average) downsample feature maps spatially, reducing computational cost and providing translation invariance by summarizing local regions.

Question 3

Which evaluation metric is most appropriate for a regression model predicting house prices when outliers are present in the data?

Accepted Answer

Mean Absolute Error (MAE)

Answer

MAE is more robust to outliers than MSE/RMSE because it uses absolute differences rather than squared differences, preventing large errors from disproportionately inflating the metric.

Question 4

What problem does batch normalization solve in deep network training?

Accepted Answer

Reduces internal covariate shift by normalizing layer inputs to have zero mean and unit variance

Answer

Batch normalization standardizes each layer's inputs across the mini-batch, stabilizing the distribution of activations and allowing higher learning rates and faster convergence.

Question 5

In the context of Shapley values (SHAP), what does a negative SHAP value for a feature indicate?

Accepted Answer

The feature decreased the model's prediction relative to the average prediction

Answer

A negative SHAP value means that feature's contribution pushed the model's output below the baseline (average prediction), indicating it reduced the predicted value for that instance.

MS-DS Master of Data science Practice Test

MS-DS Master of Data science Practice Test

MS-DS Master of Data science Machine Learning 5