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2. Statistical Learning
3. Linear Regression
4. Logistic Regression
5. Resampling Methods
6. Linear Model Selection and Regularization
7. Moving Beyond Linearity
8. Tree-Based Methods
9. Support Vector Machines
10. Unsupervised Learning
© 2019.
islr
notes and exercises from An Introduction to Statistical Learning
5. Resampling Methods
Notes
Exercises
1-4. Conceptual Exercises
5. Estimate the test error of a logistic regression model
6. Bootstrap estimates of standard errors of logistic regression coefficient estimates
7. Estimate the LOOCV error
8. Cross-validation on simulated data
9. Estimate of standard error of sample mean of
medv
in
Boston
data set