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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
10. Unsupervised Learning
Notes
Exercises
1-6. Conceptual Exercises
7. Comparison of correlation based distance and Euclidean distance on
USArrests
dataset.
8. Calculating PVE for
USArrests
dataset
9. Hierarchical Clustering on
USArrests
dataset
10. PCA and K-means on simulated data
11. Hierarchical clustering on gene expression dataset