Artificial Intelligence: Machine Learning: Software

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 front-ends for document classification (rainbow), document retrieval (arrow) and document clustering (crossbow). [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, multi-layer 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]

R, also known as `GNU S', is a free system for statistical computation and graphics similar to S. It provides a wide variety of statistical and graphical techniques (linear and nonlinear modelling, statistical tests, time series analysis, classification, and clustering).

Links to FTP repositories including ACCEL, CLASSWEB, FOCL, FOIL, GOLEM, INDEX, MILES, MOBAL, OC1, Occamn, PEBLS, RWM.

A general approach to the problem of inducing natural language parsers. It uses an annotated corpus, and produces a parser by using ILP for inducing the rules that control the actions of a shift-reduce parser. [Free]

Software toolkit for building and using motif-based hidden Markov models of DNA and proteins - from the Univ. of California-San Diego.

On this page an imlementation of Hidden Markov Models and an application to part-of-speech tagging. Also available a multivariate hypothesis testing software for Gaussian Data and TRUEVIZ: A groundtruth/metadata Editing and Visualizing Toolkit for OCR.

MEME System is a program for discovering motifs in groups of related DNA or protein sequences. MAST is a tool for searching biological sequence databases for sequences that contain one or more of a group of known motifs.

A collection of tools for creating and using HMMs for biological sequences. Free license for academic and nonprofit usages.

Software for learning Mixture Distributions. Commercial license.

Directory of software tools for modeling graphs and Bayesian networks. Some have learning capabilities.

Machine learning library for Observable Operator Models (OOMs) suitable for time-series and sequence data classification and prediction. OOMs are similar but more powerful than HMMs. [C++, BSD license]

Hidden Markov Models software library from the Center of Applied Informatics, Cologne. Includes algorithms such as Viterbi, Baum-Welch, and Forward-Backward. [C, GPL license]

A library of C++ classes for Bayesian filtering. From the Australian Centre for Field Robotics. [C++, MIT license]

A general purpose library for Bayesian filtering. [C++, LGPL license]

Platform- and data-source-independent library for embedded data mining based on the CWM/OMG and other data mining standards. XELOPES-Java algorithms: SVMs, market basket analysis, sequence analysis, decision trees, cluster analysis, multidimensional grouping. XELOPES-C++ algorithms: SVMs, decision trees. [GPL]

Computational model of human language acquisition written in Java; currently acquires a protolanguage of nouns and verbs language based on visual perception

Suite of Perl tools for counting and analyzing word n-grams in text; provides standard tests of association for identifying word n-grams in large corpora and allows users to implement other tests with minimal Perl knowledge.