Unsupervised Learning

Week 10: Oct 28 – Nov 1

Weekly Objectives

• Understand how K-means and hierarchical clustering works
• Understand the randomness in K-means and know how to deal with it
• Understand the factors that would influence clustering results
• Use built-in R functions kmeans() and hclust()
• Understand the SVD interpretation of PCA
• Practice PCA for data visualization using examples in the lecture notes

Lecture Notes and R Examples

• PCA [Source File]
• K-Means [Source File]
• Hierarchical Clustering [Source File]
• Spectral Clustering [Source File]
• Self-organizing Map [Source File]
• UMAP [Source File]
• RNA Expression Data

Homework

• Homework 10 [Source File]
• Due Nov 7, 11:59PM CT
• [Solution] will be released after Nov 11