Description:

The spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be compared with, e.g model selection, statistical tests and visual plots. This gives all the power of objects (reusability, plug together, share code) but also all the power of Matlab for machine learning research.

Changes to previous version:

Initial Announcement on mloss.org.

BibTeX Entry: Download

Supported Operating Systems: Linux, Windows

Data Formats: None

Tags: Matlab, Clustering, Regression, Support Vector Machines, Kernel Methods, Feature Selection, Multi Class

Archive: download here

Comments

Gorden Jemwa (on November 24, 2007, 21:19:30)

Excellent object-oriented design within MATLAB which provides for a intuitive interface for the beginner and a flexible extensible framework for advanced users. Some of the implementations have default values that could be problematic; for example a hard-margin SVM classifier is assumed (C=Inf), which may lead to the program stalling for real-world data sets. Also, I've had problems with the default mex optimizer interface to LIBSVM when using the one-class SVM. Changing the optimizer with the matlab interface from LIBSVM website solved the problem (one needs to extend (recommended) or modify the associated training.m accordingly). Overall, I think this is a superb effort from Jason, Goekhan, Andre and the rest of the developers in designing this environment. Most other algorithms one may need from other sources can easily be incorporated seamlessly into spider. WELL DONE!

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