Description:

MLDemos puts together a number of open-source libraries for machine learning in a single framework that allows to draw data, experiment and visualize the effects of training and model parameters.

The accent is put on the visualization and its main purpose is education and understanding of several classification, clustering and regression algorithms. Different visualization modes allow to grasp different aspects of the results obtained by the algorithms.

Attached are the Windows binaries, please refer to the website for the mac version and the source code.

NOTE: Kernel K-Means was reported to not behave as expected in the linux version.

Changes to previous version:

• Added Dynamical Systems. Drawing, Alignment and Resampling of trajectories. Regression-based dynamical systems (GMR, LWPR, SVR, GPR, MLP, KNN). Vector field display Dynamic display of generated trajectories Structure for time-dependent dynamical systems.
• Some cosmetic fixes.
• Fixed a very ugly crash with the statistic display for GPR and KNN.

BibTeX Entry: Download

Supported Operating Systems: Linux, Macosx, Windows

Data Formats: Plain Ascii

Tags: Classification, Clustering, Regression, Support Vector Machines, Visualization, Machine Learning, Gaussian Mixture Models, Pegasos, Gaussian Processes, Multi Layer Perceptron, Relevant Vector Machines

Archive: download here

Comments

Thomas Wiecki (on March 23, 2011, 14:37:51)

Tried to compile under linux (kubuntu 10.10) which worked fine, but when I try to classify with any of the classifiers I get a segfault. Also tried windows binary with wine, but no avail.

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