Chapter 12 Unsupervised Learning

Chapter learning objectives:

• Compare and contrast supervised learning and unsupervised learning.
• Perform principal component analysis to analyze the sources of variance in a dataset.
• Impute missing values in a dataset via matrix completion.
• Perform K-means clustering to partition observations into a pre-specified number of clusters.
• Perform hierarchical clustering to partition observations into a tree-like structure.