Directory of Software Resources

Home > Computers > Artificial Intelligence > Machine Learning > Software

Implementations of machine learning through algorithms in software, articles, and discussions.

Subcategories

• Belief Networks
• Data Mining
• Neural Networks
• Statistics
• Support Vector Machines

Resources in This Category

• (H)HMM Library and Designer

  http://connex.lip6.fr/%7Ebinsztok/hhld.html
  This library allows probabilistic sequence models to be constructed through use of Hidden Markov models (HMMs) and Hierarchical Markov models HMMs (HHMMs) in Ocaml programming language. [GPL]

• aiParts

  http://www.agt.net/public/bmarshal/aiparts/index.htm
  C++ classes for multi-decision problems implementing the High-Hope technique with sample programs. [MIT]

• AliceBOT

  http://alicebot.blogspot.com/
  The famous free software BOT developed in promotion of AIML (Artificial Intelligence Markup Language). [FREE]

• An Object Oriented (OOP) Framework for Neural Networks in C#

  http://www.c-sharpcorner.com/UploadFile/rmcochran/AI_OOP_NeuralNet06192006090112AM/AI_OOP_NeuralNet.aspx
  A handy basic Class and back progagator to create the framework for AI Neural Networks. [GPL]

• ArrayMiner - ClassMarker

  http://www.optimaldesign.com/ArrayMiner/ClassMarker.htm
  Programmatically isolate similarities between scattered classes of genes. Expression driven. Utilizes a voting method along with a k-Nearest-Neighbors classification. Very rich graphical interface. Samples of an unknown class are possible given enough data. Fully functional demo. [Commercial]

• Bayes Net Toolbox for Matlab

  https://github.com/bayesnet/bnt
  Supports several inference algorithms and learning algorithms. Allows simulation of static and dynamic networks, including HMMs, IOHMMs, and Kalman filters. [GPL]

• Bayes++: Open Source Bayesian Filtering Classes

  http://bayesclasses.sourceforge.net/Bayes++.html
  A library of C++ classes for Bayesian Filtering of discrete systems. [MIT]

• BETSY: A Bayesian Essay Test Scoring System

  http://edres.org/betsy
  A windows-based program that classifies text based on trained material. Designed for automated essay scoring, BETSY can be applied to any text classification task. [GPL]

• BoosTexter: A Boosting-based System for Text Categorization

  http://www.cs.princeton.edu/~schapire/boostexter.html
  A general purpose machine-learning program based on boosting for building a classifier from text and/or attribute-value data. [GPL]

• Bow: A Toolkit for Statistical Language Modeling, Text Retrieval, Classification and Clustering

  http://www.cs.cmu.edu/~mccallum/bow/
  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). [LGPL]

• C4.5 and FOIL

  http://www.rulequest.com/Personal/
  The home page of R. Quinlan with FTP links to FOIL (inductive logic programming) and C4.5 (learning decision trees). [LGPL]

• CHILL: Constructive Heuristics Induction for Language Learning

  http://www.cs.utexas.edu/users/ml/chill.html
  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]

• CMU Artificial Intelligence Repository

  http://www.cs.cmu.edu/Groups/AI/areas/learning/systems/0.html
  The Carnegie Mellon University School of Computer Science select list of a few very good machine learning systems. A list of 4 FTP repository links is also listed for exploring. [GPL]

• Designing And Implementing A Neural Network Library For Handwriting Detection, Image Analysis etc.

  http://www.codeproject.com/Articles/14342/Designing-And-Implementing-A-Neural-Network-Librar
  A concise explanation of backward propagation neural networks for handwriting analysis. Beginning functions are given for its 'Brain Net' library in VB.Net. [LGPL]

• Experience-based Language Acquisition

  http://sourceforge.net/projects/ebla
  Computational model of human language acquisition written in Java; currently acquires a protolanguage of nouns and verbs language based on visual perception. [BSD]

• Extreme Learning Machine

  http://www3.ntu.edu.sg/home/egbhuang/
  generalized Single-hidden Layer Feed forward Networks (SLFNs) and how to build them. Since work as universal approximators with adjustable hidden parameters, all parameters of ELMs can be analytically determined instead of being tuned. Written in Matlab. [GPL]

• FastMix

  http://www.cs.cmu.edu/~psand/
  Generates Gaussian mixture models for large datasets using efficient KD-clustering algorithms. [Free]

• Fuzzy machine learning framework

  http://www.dmitry-kazakov.de/ada/fuzzy_ml_synopsis.htm
  Fuzzy machine learning framework is a library of ADA packages and a GUI front-end based on graph-schemes, intuitionistic fuzzy sets and the possibility theory. Sources can be used on any platform where an Ada 2005 compiler is available. [GPL]

• GAlib: Matthew's Genetic Algorithms Library

  http://lancet.mit.edu/ga/
  A toolset of genetic algorithm objects for C++ to perform optimization. Uses any representation and genetic operators. The documentation contains implementation and examples. Nice screenshots. PVM for distributed, parallel implementations. Includes graphic examples that use the Athena, Motif widget sets, or MFC. [BSD]

• General Hidden Markov Model Library

  http://sourceforge.net/projects/ghmm
  Hidden Markov Models software library from the Center of Applied Informatics, Cologne. Includes algorithms such as Viterbi, Baum-Welch, and Forward-Backward. [GPL]

• Genetic Algorithm Projects at SourceForge.net

  http://sourceforge.net/directory/?q=Genetic+Algorithm
  A large collection of algorithm projects with complete sourcecode. [GPL]

• GMDH Shell

  https://www.gmdhshell.com/
  Provides GMDH-based machine learning technology for classification, continuous value prediction and time series forecasting. The software uses multi-core processors and HPC Linux clusters. [Commercial]

• Graclus: Efficient Graph Clustering Software

  http://www.cs.utexas.edu/users/dml/Software/graclus.html
  A fast graph clustering software that computes normalized cut and ratio association for a given undirected graph without any eigenvector computation.

• Intelligent Software Agent Projects at Sourceforge.net

  http://sourceforge.net/directory/?q=intelligent+software+agents
  A large collection of Intelligent Agent projects complete with sourcecode. [GPL]

• ITI: Incremental Tree Inducer

  http://www.cs.umass.edu/~lrn/iti/index.html
  An algorithm that incrementally constructs decision trees from labeled examples. [AFL]

• JMLR Machine Learning Open Source Software

  http://jmlr.csail.mit.edu/mloss/
  Many algorithms, toolboxes and full languages are available for scientific computing. Abstracts, PDF, and source code is available. [GPL]

• JProGraM -- PRObabilistic GRAphical Models in Java

  http://www.dii.unisi.it/%7Efreno/JProGraM.html
  JProGraM is a machine learning library which supports learning and inference algorithms for Bayesian networks, Markov random fields, hybrid random fields, probabilistic decision trees, dependency networks, and Parzen windows. [GPL]

• KEEL: Knowledge Extraction based on Evolutionary Learning

  http://sci2s.ugr.es/keel/
  The aim of this project is to develop a Computational Environment for integrating the design and use of knowledge extraction models from data using evolutionary algorithms. Genetic learning may also be applied to the model. [GPL]

• Lemga: Learning Models and Generic Algorithms

  http://www.work.caltech.edu/~ling/lemga/index.html
  A library of classes for optimizing (training) the generic models. Written in C++. Permission for use is required outside of classroom. [GPL]

• libbpfl - A Bayesian Probability Filtering Library

  http://libbpfl.sourceforge.net/
  A general purpose library for Bayesian filtering written in C++. [LGPL]

• LibML

  http://savannah.nongnu.org/projects/libml/
  A machine learning library. New implementations of various machine learning algorithms. [GPL]

• LingPipe: Natural Language Processor (NLP)

  http://www.alias-i.com/lingpipe/
  A suite of Java libraries for the linguistic analysis of human language which can link entity mentions to database entries, uncover relations, cluster documents, and discover significant trends. [GPL]

• Machine Learning (Theory)

  http://hunch.net/
  A collaborative machine learning weblog by John Langford.

• Machine Learning and Dragons - a Game

  http://www.blendedtechnologies.com/machine-learning-and-dragons-a-game/177
  A game programmed using evolutionary algorithm-based methodology allowing the game to learn by the player's decisions. There is also a method to use the alternative reinforcement learning decision tree to be used as well. Sourcecode is available for download. Python and Pygame are machine requirements. [GPL]

• Machine Learning and Inference Laboratory

  http://www.mli.gmu.edu/integrated-learning-systems-for-education-and-research-emerald-sun-version
  Downloadable group of programs comprising the EMERALD machine learning system, (Experimental Machine Example-based Reasoning and Learning Disciple) integrates five modules (e.g. or 'robots'), each displaying a capability for machine learning, visualization, and interence. [LGPL]

• Machine Learning Software Collection of Peter Clark

  http://www.cs.utexas.edu/users/pclark/software/
  Various software packages from the staff and alumni of The University of Texas at Austin which include inductions, a partial lazy evaluation, and a derivative of the Theo system. [GPL]

• Machine Learning Software Packages

  http://www.cs.cmu.edu/afs/cs/project/ai-repository/ai/areas/learning/systems/0.html
  Various classes, packages, macros and other software systems related to machine learning. [GPL]

• MALLET: Advanced Machine Learning for Language

  http://mallet.cs.umass.edu/index.php/Main_Page
  An integrated collection of Java code useful for statistical natural language processing, document classification, clustering, information extraction, and other machine learning applications to text. [GPL]

• Markov TheBeast

  http://code.google.com/p/thebeast/
  A Markov Logic Interpreter that focuses on efficient MAP inference and Online Learning featuring MAP inference using Cutting Planes combined with Max-Walk-Sat programming, parametrized weights, a shell interpreter, and cardinality constraints. [GPL]

• Matt Gerber's Predictive Technology Software Laboratory at the University of Virginia

  http://ptl.sys.virginia.edu/ptl/members/matthew-gerber/software
  Statistical servers LibLinear and SVM-light, two fast loading models for supervised classification. Also MetaPixel GUI, a front end for MetaPixel using Mono/C#. [GPL]

• Maximum Entropy Modeling Toolkit

  http://homepages.inf.ed.ac.uk/s0450736/maxent_toolkit.html
  A library of tools for constructing maximum entropy (maxent) model in either python or C++. Some program features are L-BFGS and GIS parameter estimation, and gaussian prior smoothing. [GPL]

• MEME/MAST: Motif Discovery and Search

  http://meme.sdsc.edu/meme/intro.html
  A software package to discover motifs (highly conserved regions) in groups of related DNA or protein sequences and, search sequence databases using motifs. [Commercial]

• Meta-MEME: Motif-based Hidden markov Modeling of Biological Sequences

  http://meme.sdsc.edu/meme/metameme-intro.html
  Software toolkit for building and using motif-based hidden Markov models of DNA and proteins. There is an online interactive version. Source written in C. [GPL]

• Milepost GCC Compiler

  http://ctuning.org/wiki/index.php/CTools:MilepostGCC
  A program compiler with built-in machine learning to find the most efficient compilation possible based upon the processor the program is run on. A collective optimization database, predictor web-service, and frameworks are available in order to make suggestions and further streamline the efficiency quotient of the user. This is the open source compiler that IBM has created press releases on using. [GPL]

• mloss : Machine Language Open Source Software

  http://mloss.org/software/
  A community effort listing of reproducible research via open source software, open access to data and results, and open standards for interchange. [FREE]

• MLPY Machine Learning

  http://mloss.org/software/view/66/
  A high performance Python package for predictive modeling. Fast N-dimentional array manipulation is performed via numpy using C code. New features include: OLS, Ridge Regression, Kernel Redge Regression, LASSO, LARS, Gradient descent for Regression, and K-Means. [GPL]

• mPOEMS in JAVA

  https://github.com/mr-stateradio/mpoems-in-java
  A generic framework for the evolutionary search algorithm mPOEMS. It was designed to solve optimisation problems, with an unrestricted number of objectives. This site provides all sources and some exemplary implementations, e.g. of the n-hard knapsack problem. [AFL]

• NEITHER: A Propositional Theory Refinement

  http://www.cs.utexas.edu/users/ml/neither.html
  A system to modify an incomplete or incorrect rule base to make it consistent with a set of input training examples. Written in C++ [Free]

• Neural Networks Prediction Software

  http://www.altredo.com/
  Innovative neural networks stock prediction web-based software. Free trial. [Commercial]

• New Scientific Brainstorming Software for Inventors -- Windows, Mac and Linux

  http://www.paramind.net/pmscientificversion.html
  A software developed to help your team brainstorm. Words are replaced programmatically in user's idea sentence with new words from program categories perhaps creating ideas not formerly thought of. Includes word categories. [Commercial]

• Nieme: Classification, Regression, Ranking and Reinforcement Learning

  http://nieme.lip6.fr/
  A machine learning library for classification, regression, ranking and reinforcement learning. It implements several well-known algorithms and is specially designed for large-scale applications. [GPL]

• Nonparametric Classification with Polynomial MPMC Cascades

  http://cervisia.org/machine_learning_code.php
  Scalable non-parametric classification with Polynomial MPMC Cascades for use in Matlab. [GPL]

• NSP: N-gram Statistics Package

  http://www.d.umn.edu/~tpederse/nsp.html
  Software for counting and analyzing word n-grams in text. This package provides standard tests of association for identifying word n-grams in large corpora and allows users to implement other tests with minimal scripting knowledge. Written in Perl. [GPL]

• Numenta

  http://numenta.com/
  Software that provides a high level of automation in analyzing streaming data, the ability to learn continuously from data, and the ability to drive action from the output of Grok's data models.

• Open Source Computer Vision Library

  http://sourceforge.net/projects/opencvlibrary/
  Open source computer learning system making use of the Bayesian inferencing engine. [GPL]

• OpenCyc

  http://www.opencyc.org/
  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 wide variety of intelligent applications including; rapid development of an ontology in a vertical area, email prioritizing, routing, summarization, and annotating, expert systems, game engine development. [GPL]

• ORANGE: Inter-active Machine Learning Data Mining components

  http://www.ailab.si/orange
  A component based framework for data input/output, preprocessing, predictive modelling, ensemble methods, and modelling validation. [GPL]

• Pattern Matching Pointers

  http://www.cs.ucr.edu/~stelo/pattern.html
  Using algorithms to address issues of searching and matching strings and more complicated patterns such as trees, regular expressions, graphs, point sets, and arrays. [GPL]

• PRAPI: Pattern Recognition Application Programmer's Interface

  http://www.ee.oulu.fi/~topiolli/cppdocs/
  A library for many pattern recognition tasks. The main focus of this package is on image analysis but utilizes a general architecture and XML-based data interchange format. Written in C++ [GPL]

• PRODIGY: An Architecture for Planning and Learning

  http://www.cs.cmu.edu/afs/cs.cmu.edu/project/prodigy/Web/prodigy-home.html
  A system of research planning and learning utilizing explanation-based learning, partial evaluation, experimentation, graphical knowledge acquisition, automatic abstraction, mixed-initiative planning, and case-based reasoning. [Free]

• QSMM State Machine Model

  http://qsmm.org/
  A Boltzmann machine based framework for development of non-deterministic intelligent state models. [GPL]

• Rapid Miner

  http://rapid-i.com/
  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 a graphical XML based user interface. (Formerly YALE) [GPL]

• Scalable Machine Learning for Massive Datasets: Fast Summation Algoritms

  http://www.umiacs.umd.edu/labs/cvl/pirl/vikas/Current_research/scalable_machine_learning/scalable_machine_learning.html
  Several algoritms with papers on Fast kernel density estimation, Improved Fast Gauss Transformation, and Fast ranking. Some unpublished papers are also included. [GPL]

• Scikit-learn

  http://scikit-learn.org/
  An open source Python library that implements a range of machine learning, preprocessing, cross-validation and visualization algorithms using a unified interface. Provides documentation and source code.

• Self-Taught: Software That Learns By Doing

  http://www.computerworld.com/s/article/108320/Self_Taught_Software_That_Learns_By_Doing?taxonomyId=018
  Short article on self-modifying software touching on co-training, partial-programming, and genetic programming (GP) methods of problem solving. [FREE]

• SenseClusters

  http://senseclusters.sourceforge.net/
  Programs to cluster similar contexts together using unsupervised knowledge-lean methods for word sense discrimination, email categorization, and name discrimination. Written in Perl. [GNU]

• shogun

  http://www.shogun-toolbox.org/
  A generic SVN object interface with many implementations including OCAS, Liblinear, LibSVM, SVMLight, SVMLin, and GPDT. Each SVN provides implementations of the most common kernals such as Linear, Ploynomial, Gaussian, and Sigmond Kernel. Implemented in C++ and interfaces to Matlab, R, Octave and Python. [GPL]

• SMILE (Structural Modeling, Inference, and Learning Engine) with GeNIe

  http://genie.sis.pitt.edu/
  SMILE (Structural Modeling, Inference, and Learning Engine) is a fully portable library of C++ classes implementing graphical decision-theoretic methods, such as Bayesian net-works and influence diagrams, directly amenable to inclusion in intelligent systems. Its Windows user interface, GeNIe is a versatile and user-friendly development environment for graphical decision-theoretic models. Both modules, developed at the Decision Systems Laboratory, University of Pittsburgh. Registration is required for download. [GPL]

• Software Learning Projects at NASA

  http://code.nasa.gov/
  A resource for open source software at NASA

• Software Packages for Graphical Models/Bayesian Networks

  http://www.ai.mit.edu/~murphyk/Software/bnsoft.html
  Tools for modeling graphs and Bayesian networks. Scroll down. [AFL], [Commercial]

• Sorting Algorithms for Machine Learning

  http://www.csse.monash.edu.au/~lloyd/tildeAlgDS/Sort/
  Various sorting algorithms including insertion, quick, merge, heap, Dutch National Flag, and radix with on-line demos. [Free]

• Spider: General Purpose Machine Learning Toolbox in Matlab

  http://www.kyb.tuebingen.mpg.de/bs/people/spider/index.html
  An object orientated environment for machine learning in Matlab. Algorithms can be plugged together and can be compared with (e.g. model selection, statistical tests and visual plots). Algorithms may be downloaded separately. [GPL]

• SUBDUE: Graph Based Knowledge Discovery

  http://ailab.wsu.edu/subdue/
  A program which discovers interesting and repetitive subgraphs in labeled graph representations using the minimum description length principle. Includes applications to molecular biology. [Free]

• The AutoClass Project

  http://ti.arc.nasa.gov/tech/rse/synthesis-projects-applications/autoclass/
  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]

• The Leibniz Software System

  http://www.utdallas.edu/~klaus/Leibnizprogram/leibnizmain.html
  A formal system for constructing artificial intelligent software agents from the book, 'Design of Logic-based Intelligent Systems' covering such topics as production rules, neural nets, support vector machines, fuzzy logic, and Bayesian networks. License is given through purchase of the book alone. [COMM]

• The Lisa Project

  http://lisa.sourceforge.net/
  A production rule based system implemented in a Common Lisp Object System (CLOS) for the development of Lisp based intelligent software agents. [LGPL]

• The Torch Machine Learning Library

  http://www.torch.ch/
  This package forms a complete gradient descent machine learning library. Modules support vector machines in classification and regression, ensemble models such as bagging or adaboost, non-parametric models such as K-nearest neighbors, Parzen regression, and Parzen density estimation. Includes speech recognition tools. Written in C++ [BSD]

• TIMBL: Tilburg Memory Based Learner

  http://ilk.uvt.nl/software.html
  A program implementing several memory-based learning techniques. These learners store representation of the training set explicitly, and classifies new cases by extrapolation from the most similar stored cases. [AFL]

• Titan: Distributed Graph Database

  http://thinkaurelius.github.io/titan/
  A Highly Scalable, Distributed Open Source Storage Database providing index free adjacency. [AL]

• Tree Visualizer

  http://www.sgi.com/tech/mlc/trees.html
  Software which allows one to navigate (fly) through the data tree, zoom in on interesting nodes, click on bars to get counts, and mark interesting places in the tree. Includes datasets for automobiles, voting, produce, and medical research. Uses LEDA, ([AFL] licensed only). [GPL]

• UCI Machine Learning

  http://www.ics.uci.edu/~mlearn/MLRepository.html
  A repository of databases, domain theories and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms at the University of California at Irvine. [Free]

• UMDHMM and other statistical programs

  http://www.kanungo.com/software/software.html
  This tool implements Hidden Markov Models and application to part-of-speech tagging. Also available; a multivariate hypothesis testing software for gaussian data, and a groundtruth/metadata editing and visualizing toolkit for OCR. [GPL]

• VIBES: Variational Inference for Bayesian Networks

  http://vibes.sourceforge.net/
  A software package which allows variance-modeled posterior inference to be performed automatically on a Bayesian network. [GPL]

• Weka 3: Data Mining Software

  http://www.cs.waikato.ac.nz/~ml/weka/index.html
  A collection of tools that implement decision trees and tables, rule learners, Naive Bayes, support vector machines, voted perceptrons, multi-layer perceptron. Meta schemes include bagging, stacking, and boosting. Written in Java. [GPL]

• What If: Web-based Scientific Discovery

  http://swift.cmbi.ru.nl/servers/html/index.html
  An algorithm engine which will calculate everything from symmetry, torsion angles, polar fraction through protein analysis and bond angles. Online version only. [Free]

• WinMine Toolkit

  http://research.microsoft.com/~dmax/WinMine/tooldoc.htm
  A set of tools for Windows 2000/NT/XP that allow you to build statistical models from data. [Free]

• Zinnia

  http://zinnia.sourceforge.net/
  Small portable online hand recognition system based on Support Vector Machines. Provides a relatively small machine model running at 50-100 char per second recognition speed. [BSD]

 

Home > Computers > Artificial Intelligence > Machine Learning > Software

 

---

 

Thanks to DMOZ, which built a great web directory for nearly two decades and freely shared it with the web. About us