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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
4. Logistic Regression
Notes
Exercises
1-9. Conceptual Exercises
10. Classifying
Direction
in the
Weekly
dataset
11. Classifying high/low
mpg
cars in
Auto
dataset
13. Classifying high crime rate using the
Boston
dataset