INTRODUCTION TO CLUSTERING AND CLASSIFICATION: This lecture provides an overview of the basic concepts behind supervised and unsupervised learning algorithms. Included is a discussion of k-means and knn (k-nearest neighbors).

MATLAB COMMANDS

`SVD PCA KMEANS KNNSEARCH`

ADVANCED CLUSTERING AND CLASSIFICATION: Classification algorithms such as Gaussian mixture models, Naive Bayes and Boosting are considered in these examples. Training and cross-validation are also considered.

MATLAB COMMANDS

`FITGMDIST CLUSTER FITNAIVEBAYES NB.PREDICT CLASSIFY`