Roger Jang

Introduction

This toolbox provides a number of important functions for DCPR (data clustering and pattern recognition). Click here to download the whole toolbox.

Interesting Demos

After downloading the toolbox, you may want to try some of the interesting demos:

• gmmTrainDemo2dCovType01: Animation of GMM (Gaussian mixture models) training with isotropic covariance matrices
• gmmTrainDemo2dCovType02: Animation of GMM (Gaussian mixture models) training with diagonal covariance matrices
• gmmTrainDemo2dCovType03: Animation of GMM (Gaussian mixture models) training with full covariance matrices
• gmmGrowDemo: Animation of GMM (Gaussian mixture models) growing with center splitting
• hClusteringDemo: Step-by-step hierarchical clustering

gdDemo: Interactive demo of gradient descent over the peaks function taylorExpansionDemo: Interactive demo of polynomial fit and taylor expansios lcs and editDistance: Visualize the result of dynamic programming for LCS (longest common subsequence) and ED (edit distance)

Citation

If you are using the toolbox for your research, please kindly give reference as follows:

Jyh-Shing Roger Jang, "DCPR (Data Clustering and Pattern Recognition) Toolbox", available from the link at the author's homepage at "http://www.cs.nthu.edu.tw/~jang".

Documentation

Here are some docs of the toolbox:

• On-line tutorial on "Data Clustering and Pattern Recognition" using the toolbox, with many examples.
• Toolbox document generated by m2html