What is the role of feature selection in modeling?

What is the role of feature selection in modeling?

Feature selection helps improve model performance by selecting the most relevant features, reducing overfitting.

Why is it important to reduce overfitting?

Reducing overfitting ensures that the model generalizes well to unseen data, improving its predictive accuracy.

What methods are commonly used for feature selection?

Common methods include filter methods, wrapper methods, and embedded methods, each with its own advantages.

Can feature selection impact model training time?

Yes, by reducing the number of features, feature selection can significantly decrease training time.

How do I know which features to select?

You can use techniques like correlation analysis, recursive feature elimination, or model-based feature importance.