Lecture 17 - Clustering and Density Estimation#

Objectives#

  • Define unsupervised learning.

  • Define the clustering problem.

  • Use the k-means algorithm to solve the clustering problem.

  • Explain the density estimation problem.

  • Solve the density estimation problem using the Gaussian mixture model.

  • Use the Bayesian information criterion to select the number of mixture components in a density estimation problem.