Machine Learning and Data Science Quiz

They have a tendency to overfit and capture complex decision boundaries with small trees (correct)

They are fast to train but have low interpretability

They are highly interpretable and prone to underfitting

They are slow to train and have a high bias

Boosting

Bayes Classifier (correct)

Bagging

Random Forest

To create highly interpretable models

To reduce the complexity of decision boundaries

To improve prediction accuracy by combining multiple models (correct)

To speed up the training process of individual models

<p>CS109A Introduction to Data Science by Pavlos Protopapas</p> Signup and view all the answers

<p>Overfitting and capturing complex decision boundaries</p> Signup and view all the answers