Research Groups

VIBES: Variational Inference for Bayesian Networks VIBES: Variational Inference for Bayesian Networks- A software package which allows variance-modeled posterior inference to be performed automatically on a Bayesian network. [GPL] OpenCyc OpenCyc- Open source version of the Cyc technology, the world's largest and most complete general knowledge base and commonsense reasoning engine. Can be used as the basis of a wi… ORANGE: Inter-active Machine Learning Data Mining components ORANGE: Inter-active Machine Learning Data Mining components- A component based framework for data input/output, preprocessing, predictive modelling, ensemble methods, and modelli… Sorting Algorithms for Machine Learning Sorting Algorithms for Machine Learning- Various sorting algorithms including insertion, quick, merge, heap, Dutch National Flag, and radix with on-line demos. [Free] LingPipe: Natural Language Processor (NLP) LingPipe: Natural Language Processor (NLP)- A suite of Java libraries for the linguistic analysis of human language which can link entity mentions to database entries, uncover rel… Bayes++: Open Source Bayesian Filtering Classes Bayes++: Open Source Bayesian Filtering Classes- A library of C++ classes for Bayesian Filtering of discrete systems. [MIT] Spider: General Purpose Machine Learning Toolbox in Matlab Spider: General Purpose Machine Learning Toolbox in Matlab- An object orientated environment for machine learning in Matlab. Algorithms can be plugged together and can be compared… (H)HMM Library and Designer (H)HMM Library and Designer- This library allows probabilistic sequence models to be constructed through use of Hidden Markov models (HMMs) and Hierarchical Markov models HMMs (HH… KEEL: Knowledge Extraction based on Evolutionary Learning KEEL: Knowledge Extraction based on Evolutionary Learning- The aim of this project is to develop a Computational Environment for integrating the design and use of knowledge extrac… Rapid Miner Rapid Miner- The Rapid Miner toolset is an environment for machine learning through use of nested operators. Multiple experiments can be arbitrarily nested together through use of… Nonparametric Classification with Polynomial MPMC Cascades Nonparametric Classification with Polynomial MPMC Cascades- Scalable non-parametric classification with Polynomial MPMC Cascades for use in Matlab. [GPL] Maximum Entropy Modeling Toolkit Maximum Entropy Modeling Toolkit- A library of tools for constructing maximum entropy (maxent) model in either python or C++. Some program features are L-BFGS and GIS parameter es… MEME/MAST: Motif Discovery and Search MEME/MAST: Motif Discovery and Search- A software package to discover motifs (highly conserved regions) in groups of related DNA or protein sequences and, search sequence database… BETSY: A Bayesian Essay Test Scoring System BETSY: A Bayesian Essay Test Scoring System- A windows-based program that classifies text based on trained material. Designed for automated essay scoring, BETSY can be applied to … TIMBL: Tilburg Memory Based Learner TIMBL: Tilburg Memory Based Learner- A program implementing several memory-based learning techniques. These learners store representation of the training set explicitly, and class… NSP: N-gram Statistics Package NSP: N-gram Statistics Package- Software for counting and analyzing word n-grams in text. This package provides standard tests of association for identifying word n-grams in large… Experience-based Language Acquisition Experience-based Language Acquisition- Computational model of human language acquisition written in Java; currently acquires a protolanguage of nouns and verbs language based on v… libbpfl - A Bayesian Probability Filtering Library libbpfl - A Bayesian Probability Filtering Library- A general purpose library for Bayesian filtering written in C++. [LGPL] General Hidden Markov Model Library General Hidden Markov Model Library- Hidden Markov Models software library from the Center of Applied Informatics, Cologne. Includes algorithms such as Viterbi, Baum-Welch, and Fo… Software Packages for Graphical Models/Bayesian Networks Software Packages for Graphical Models/Bayesian Networks- Tools for modeling graphs and Bayesian networks. Scroll down. [AFL], [Commercial] CHILL: Constructive Heuristics Induction for Language Learning CHILL: Constructive Heuristics Induction for Language Learning- A general approach to the problem of inducing natural language parsers. It uses an annotated corpus, and produces a… Machine Learning Software Packages Machine Learning Software Packages- Various classes, packages, macros and other software systems related to machine learning. [GPL] PRODIGY: An Architecture for Planning and Learning PRODIGY: An Architecture for Planning and Learning- A system of research planning and learning utilizing explanation-based learning, partial evaluation, experimentation, graphical… NEITHER: A Propositional Theory Refinement NEITHER: A Propositional Theory Refinement- A system to modify an incomplete or incorrect rule base to make it consistent with a set of input training examples. Written in C++ [Fr… Weka 3: Data Mining Software Weka 3: Data Mining Software- A collection of tools that implement decision trees and tables, rule learners, Naive Bayes, support vector machines, voted perceptrons, multi-layer p… ITI: Incremental Tree Inducer ITI: Incremental Tree Inducer- An algorithm that incrementally constructs decision trees from labeled examples. [AFL] FastMix FastMix- Generates Gaussian mixture models for large datasets using efficient KD-clustering algorithms. [Free] WinMine Toolkit WinMine Toolkit- A set of tools for Windows 2000/NT/XP that allow you to build statistical models from data. [Free] Bow: A Toolkit for Statistical Language Modeling, Text Retrieval, Classification and Clustering Bow: A Toolkit for Statistical Language Modeling, Text Retrieval, Classification and Clustering- A library of C code useful for writing statistical text analysis, language modelin… UCI Machine Learning UCI Machine Learning- A repository of databases, domain theories and data generators that are used by the machine learning community for the empirical analysis of machine learning…