Roger Jang and MIR Lab

Introduction

This toolbox (MLT, or Machine Learning Toolbox) provides a number of essential functions for machine learning. You can download the toolbox here.

Documentation

• Within MATLAB:
  • Type "mltDoc" to see
    • Tutorial for getting started
    • User guide
    • Application notes
    • Function reference
    Or type "doc" and navigate to the home page. At the bottom right of the home page, under Supplemental Software, click the link to "Machine Learning Toolbox". (You need to add the toolbox to the search path first.)
  • Type "mltDoc command" for getting online help. For instance, try "mltDoc nbcTrain" to get the help of training a naive Bayes classifier.
• On-line tutorials using the toolbox, with many application examples:
  • Data Clustering and Pattern Recognition
    • Leaf Recognition
    • Human Identification
    • Finger-Ready Detection
    • Emoticon Mood Recognition
  • Audio Signal Processing and Recognition
    • Coin Type Recognition
    • Singing Type Classification
    • Tone recognition
    • Music genre classification
    • Lexical stress detection

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
• hierClusteringPlot: Step-by-step hierarchical clustering

gradientDescentDemo: 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, "Machine Learning Toolbox", available at "http://mirlab.org/jang/matlab/toolbox/machineLearning", accessed on [date].

Trouble shooting

If you run into the problem of "Invalid MEX-file... The specified module could not be found" under MS Windows, please install Visual C++ runtime at http://www.microsoft.com/en-us/download/details.aspx?id=30679.