Wandora is a general purpose data extraction, management, and publishing application based on Topic Maps and Java. Wandora has a graphical user interface, layered presentation of knowledge, several data storage options, rich data extraction, import and export capabilities, and an embedded HTTP server that enables dynamic publication of Topic Maps. Wandora is well suited for rapid ontology construction and knowledge mashups.
SHOGUN is a machine learning toolbox whose focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It provides a generic SVM object interfacing to several different SVM implementations, all making use of the same underlying, efficient kernel implementations. Apart from SVMs and regression, SHOGUN also features a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons, and algorithms to train hidden Markov models. SHOGUN can be used from within C++, Matlab, R, Octave, and Python.
Lush is a Lisp dialect with extensions for object-oriented and array-oriented programming. It is intended as a programming environment for prototyping numerically intensive applications. Unlike alternatives like Python or SciLab, Lush is designed for easy integration of existing C/C++/Fortran codes.
Evolving Games for Unnatural Intelligence is a Java package for unsupervised machine learning based on Evolutionary Game Theory on directed graphs. It is able to segment data without any previuos information on the number of segments. It has no GUI, but implements generalizations of the original method proposed by Li, Chen, He and Jiang in the arxiv paper "A Novel Clustering Algorithm Based Upon Games on Evolving Network", published on 30 Dec 2008.
Optimization Algorithm Toolkit is a workbench and toolkit for developing, evaluating, and playing with classical and state-of-the-art optimization algorithms on standard benchmark problem domains. It includes reference algorithm implementations, graphing, visualizations, and much more.
Trans (short for Transmuter Programming Language) is an extremely dynamic, biologically-inspired prototyping language providing a framework for experimenting with naturally evolving systems of objects over the net, and for exploring new ideas about recombinant software, code morphing, and evolutionary programming. Trans is also a very capable general-purpose programming language. It's fast, flexible, compact, object-oriented, highly extensible, and easy-to-learn. It can be used for rapid prototyping, or as a scripting language, an embedded language, a network server or client, a system of cooperating network nodes, a real-time control and monitoring system, and more.
PCP (Pattern Classification Program) is a machine learning program for supervised classification of patterns. It runs in interactive and batch modes, and implements the following machine learning algorithms and methods: k-means clustering, Fisher's linear discriminant, dimension reduction using Singular Value Decomposition, Principal Component Analysis, feature subset selection, Bayes error estimation, parametric classifiers (linear and quadratic), pseudo-inverse linear discriminant, k-Nearest Neighbor method, neural networks, Support Vector Machine algorithm (SVM), model selection for SVM, cross-validation, and bagging (committee) classification.