: Explores associations and patterns without defined outcome measures, covering techniques like spectral clustering and non-negative matrix factorization.

: It provides deep dives into the bias-variance tradeoff , model assessment, and selection pitfalls. Key Authors and Their Impact

: Developed generalized additive models. Tibshirani famously proposed the Lasso method.

: Focuses on predicting outcomes based on input measures. Topics include linear regression, classification trees, neural networks, and Support Vector Machines (SVMs) .