Applied Predictive Modeling

A comprehensive guide to the principles and practices of building robust predictive models. Tailored for practitioners and data scientists, the book blends theoretical foundations with practical applications across various domains, including healthcare, finance, and marketing. Covering essential topics such as data preprocessing, feature engineering, model evaluation, and advanced machine learning techniques, the book emphasizes real-world problem-solving with clear examples and R code implementations. This resource is indispensable for anyone aiming to master predictive analytics and develop models that drive actionable insights.