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