Statistical Learning: 5.1 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 Cross-validation and the Bootstrap 2:32 Training Error versus Test error 3:27 Training- versus Test-Set Performance 6:57 More on prediction-error estimates 8:11 Validation-set approach 8:58 The Validation process 9:55 Example: automobile data 13:14 Drawbacks of validation set approach