Statistical Learning: 5.2 K-fold Cross Validation
Statistical Learning, featuring Deep Learning, Survival Analysis and Multiple Testing Trevor Hastie, Professor of Statistics and Biomedical Data Sciences at Stanford University - https://statistics.stanford.edu/peopl... Robert Tibshirani, Professor of Statistics and Biomedical Data Sciences at Stanford University - https://statistics.stanford.edu/peopl... Jonathan Taylor, Professor Statistics at Stanford University - https://statistics.stanford.edu/peopl... You are able to take Statistical Learning as an online course on EdX, and you are able to choose a verified path and get a certificate for its completion. You can choose to take the course in R (https://www.edx.org/course/statistica) or in Python (https://www.edx.org/learn/data-analys...) For more information about courses on Statistics, you can browse our Stanford Online Catalog: https://stanford.io/3QHRi72 0:00 Introduction 0:55 K-fold Cross-validation in detail 2:31 The details 4:07 A nice special case! 6:59 Auto data revisited 8:16 True and estimated test MSE for the simulated data 10:52 Cross-Validation for Classification Problems
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