Assignment 8 CS 750/850 Machine Learning solved

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Problem 1 [33%]
Describe, in words, the results that you would expect if you performed K-means clustering of the eight
shoppers in Figure 10.14 in ISL, on the basis of their sock and computer purchases, with K = 2. Give three
answers, one for each of the variable scalings displayed. Explain.
Problem 2 [33%]
In this problem, you will compute principal components for the Auto dataset. First remove qualitative
features, which cannot be handled by PCA. Then:
1. Compute principal components without scaling features. Plot the result (you can use
2. Compute principal components after scaling features to have unit variance. Plot the result (you can use
3. How do the principal components computed in parts 1 and 2 compare?
Problem 3 [33%]
1. Apply PCA to a subset of the MNIST dataset. Plot the first few principal vectors. Describe what you
observe and interpret the results.
2. Optional(+10 points): Apply k-means clustering to the MNIST dataset both with the original features,
and using at least two different subsets of the principal components. Which approach works best?