This foundational text explores feature selection methods crucial for high-dimensional datasets, essential for churn prediction.

A comprehensive guide to statistical learning techniques, this book covers essential concepts that underpin feature selection.

This practical book offers insights into predictive modeling, including feature selection techniques relevant to churn analysis.

Bishop's work introduces key concepts in machine learning, providing a solid theoretical background for feature selection.

Murphy's book offers a probabilistic approach to machine learning, encompassing feature selection methods and their applications.

This classic text covers data mining techniques, including feature selection strategies vital for customer churn prediction.

A practical guide to feature engineering, this book emphasizes feature selection as a key component of successful machine learning.

An accessible introduction to statistical learning, offering insights into feature selection techniques and model evaluation.

This book provides a conceptual framework for data science, emphasizing the importance of feature selection in model building.

An in-depth exploration of feature selection methods from a data-centric viewpoint, crucial for improving model performance.