Скачать с ютуб Intro to Statistical Learning (2nd Ed), Solution to Problem 6.3C | Error with Ridge regression в хорошем качестве

Intro to Statistical Learning (2nd Ed), Solution to Problem 6.3C | Error with Ridge regression

6.3C Suppose we estimate the regression coefficients in a linear regression model by minimizing ∑i=1n(yi−β0−∑j=1pβjxij)2+λ∑j=1pβ2j for a particular value of λ . For parts (a) through (e), indicate which of i. through v. is correct. Justify your answer. (a) As we increase λ from 0, the training RSS will: i. Increase initially, and then eventually start decreasing in an inverted U shape. ii. Decrease initially, and then eventually start increasing in a U shape. iii. Steadily increase. iv. Steadily decrease. v. Remain constant. (b) Repeat (a) for test RSS. (c) Repeat (a) for variance. (d) Repeat (a) for (squared) bias. (e) Repeat (a) for the irreducible error. Colab (R): https://colab.research.google.com/dri... My GitHub (R): https://github.com/nicklausmillican/I... My GitHub (Python): https://github.com/nicklausmillican/I... Download Book: https://www.statlearning.com/ Authors' Lectures (R):    • Statistical Learning with R   Authors' Lectures (Python):    • Statistical Learning with Python