A multi-lingual toolkit for various decision tree algorithms with C++ libraries. Available for free download for a variety of platforms.

Client-server Java based data mining software for mining association rules. Developed at University of Massachusetts.

An unsupervised Bayesian classification system that seeks a maximum posterior probability classification.

A decision tree tool that automatically sifts large, complex databases, searching for and isolating significant patterns and relationships. Offers free limited capability demo for download, product features, applications, user feedback, and associated books.

A small Excel based freeware to build Classification Tree models in Excel. Uses C4.5 algorithm. Very easy to learn and use - but capability is limited.

A freely available software toolkit for clustering low- and high-dimensional data sets. It is well-suited for clustering data sets arising in many areas including information retrieval, customer purchasing transactions, science, and biology.

Collection of standalone data mining programs, available as scripts or Java programs. Contains information for downloading, installation, data preparation, and operating instructions. Supplementary to the book titled Predictive Data Mining - A Practical Guide.

Open source software for extraction and reporting using a powerful template tool. Deft combines declarative concepts of SQL with all of Perl's features. Requires Linux and Perl

Includes source code, related papers and associated projects.

Written in Python, the toolbox handles caching of database queries and parallelism within a collection of independent queries. Our toolbox provides a number of routines for basic data mining tasks on top of which the user can add more functions - mainly domain and data collection dependent - for complex and time consuming data mining tasks. GNU/GPL. From the Computer Sciences Laboratory of The Australian National University

Source code for program for creation of hierarchical classification trees. Information about implementations, documentation, and related research papers.

Source code for decision tree algorithms from Ross Quinlan's homepage, available free for download.

Frequent itemset and association rule mining implementations (C++) such as Apriori, Eclat and FP-growth.

A Microsoft Access application designed to provide tools to explore your databases with graphs and queries. It is also a quick way to generate/prototype Access Graphs without running the Wizards.

Includes source code, related research papers and associated work.

MLC++ is a standard C++ library for supervised machine learning, with back-end and front-end tools for data mining tasks like Decision Trees, and Clustering. Information on legal issues, mailing lists, history, standards, platform support, and download instructions.

Model based clustering and discriminant analysis, including hierarchical clustering and EM. Developed at University of Washington.

A freely available software toolkit for finding frequent patterns in diverse datasets. It contains highly efficient algorithms for finding patterns in transactional, sequential, and graph datasets.

Open Source creation of a data mining C++ procedure library. Initially focused on mining generalised association rules and generalised sequential patterns

A Software system for data mining based on rough set theory. GUI based operation on MS Windows platforms, with a wide variety of algorithms. Information on features, documentation, utilities, and upcoming releases.

Modelling tool that analyzes data generating classification, regression or class probability prediction models.

Uses the Minimum Message Length (MML) principle to do mixture modeling. Mixture modeling concerns modeling a statistical distribution by a mixture of other distributions, and is also known as unsupervised concept learning in Artificial Intelligence. Links to related research papers and software.

Environment for statistical computing and dynamic graphics based on Lisp. Contains contributed code and submission instructions.

Windows software tool that induces rules using the PNC2 cluster algorithm. An integrated parameter tuning component allows an easy adjustment of the algorithm's behaviour to the given problem without any further knowledge. [Gnu GPL]

Software suite which has algorithms for association rules, building classifiers, and clustering data from relational database products using JDBC. References to related articles, and research papers.

The VisDB has been developed to support the exploration of large database. The VisDB system implements several visual data mining techniques, allowing an exploration of large databases (up-to about one million data values).

Data Mining applications developed with Visual Basic or the .NET Framework by Kingsley Tagbo, including Naive Bayes Classifiers. Site provides public domain data mining applications with source code and online documentation. The latest release as of October 2002 is 'Visual Basic Data Mining With Naive Bayes' and '.NET Data Mining With Naive Bayes'.

By David Chickering at Microsoft Research. The WinMine Toolkit is a set of tools for Windows 2000/NT/XP that allow you to build statistical models from data. The majority of the tools are command-line executables that can be run in scripts.

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]

A public-domain software package for the interactive visual exploration of multivariate data sets. It is available on all UNIX platforms which support XR4 or higher. The current version of the software (3.1) supports scatterplots, star glyphs, parallel coordinates, and dimensional stacking.