What is feature selection and why is it important in different domains?

What is feature selection and why is it important in different domains?

Feature selection is the process of selecting a subset of relevant features for model training. It's crucial because it helps improve model performance, reduces overfitting, and decreases training time.

Can you give examples of how feature selection is applied in different fields?

Sure! In healthcare, feature selection can identify key biomarkers for disease prediction. In finance, it helps in selecting indicators for stock price prediction.

What techniques are commonly used for feature selection?

Common techniques include filter methods, wrapper methods, and embedded methods. Each has its strengths depending on the dataset and model.

How does feature selection impact model accuracy?

Effective feature selection can significantly enhance model accuracy by eliminating irrelevant or redundant features, leading to better generalization.