A library of C code useful for writing statistical text analysis, language modeling and information retrieval programs. The current distribution includes the library, as well as frontends for document classification (rainbow), document retrieval (arrow) and document clustering (crossbow). [Free]
Takes a database of cases described by a combination of real and discrete valued attributes, and automatically finds the natural classes in that data. It can be seen as a Naive Bayes classifier where the class node is hidden. [Free]
Tools for learning dependency networks or Bayesian networks from data. [Free]
Supports several inference algorithms and learning algorithms. Allows simulation of static and dynamic networks, including HMMs, IOHMMs, and Kalman filters.
Generates Gaussian mixture models for large datasets using efficient EM clustering algorithms. [Free]
An algorithm that incrementally constructs decision trees from labeled examples. [Free for individual research purposes]
Suite that implements decision trees and tables, rule learners, Naive Bayes, support vector machines, voted perceptrons, multilayer perceptron. Meta schemes include bagging, stacking, and boosting. [Free under GPL]
A propositional theory refinement system that will modify a incomplete or incorrect rule base so as to make it consistent with a set of input training examples. [Free]
A software package developed at MIT Lincoln Laboratory which integrates more than 20 neural network, statistical, and machine learning classification, clustering, and feature selection algorithms into a modular software package. [Public domain license]
An architecture for planning and learning. [Free]
