A. The types of feature selection for dimensionality reduction include: a.Filter Methods: Use statistical measures to score and select features (e.g., correlation, chi-square). b.Wrapper Methods: Use model performance to evaluate feature subsets (e.g., recursive feature elimination). c.Embedded Methods: Perform feature selection during the model training (e.g., Lasso regression).