 Model selection and validation 1: Cross-validation

By Ryan Tibshirani.

Online text: www.stat.cmu.edu/~ryantibs/datamining/lectures/18-val1.pdf

Cited passages: Model selection and validation 1: Cross-validation, slides 5–8 and 11–14: tuning for prediction, training error and refitting on each training fold; Model selection and validation 1: Cross-validation, slides 6–8 and 11–14: fresh-response error, training error and held-out scoring.