A MATLAB spectral clustering package to deal with large data sets. Our tool can handle large data sets (200,000 RCV1 data) on a 4GB memory general machine. Spectral clustering algorithm has been [...]

A K-means clustering implementation for Python, Matlab and C. This algorithm yields the very same solution as standard Kmeans, even after each iteration. However it uses some triangle inequalities [...]

A C++ toolkit containing machine learning algorithms and tools that facilitate creating complex software in C++ to solve real world problems.

A C++ library of machine learning algorithms and tools, and several demos that show how to use it.

This is an implementation of variational Dirichlet process Gaussian mixtures. Thus, this works like the k-means, but it searched for the number of clusters as well. Couple algorithms are [...]

The High-Dimensional Data Clustering (HDDC) toolbox contains an efficient unsupervised classifier for high-dimensional data. This classifier is based on a mixture of Gaussian models adapted for [...]

Orange is a component-based machine learning and data mining software. It includes a friendly yet powerful and flexible graphical user interface for visual programming. For more advanced use(r)s, [...]

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 [...]

RapidMiner (formerly YALE) is one of the most widely used open-source data mining suites and software solutions due to its leading-edge technologies and its functional range. Applications of [...]

The Weka workbench contains a collection of visualization tools and algorithms for data analysis and predictive modelling, together with graphical user interfaces for easy access to this [...]