Machine learning for access and retrieval II

Lecture slides:

• Hidden Markov Models with Applications
• Outline
• Clustering by Mixture Models
• Clustering
• Approaches to Clustering
• Mixture Model-based Clustering
• Mixture of Normals
• Advantages
• EM Algorithm
• EM for the Mixture of Normals
• Computation Issues
• Examples
• Classification Likelihood
• Classification EM
• Outline

Author: Jia Li, Pennsylvania State University