Computers - Artificial Intelligence

Software
Windows
Linux

Help
Contact
Legal

Computers - Artificial Intelligence - Machine Learning

Knowledge Discovery Central - Knowledge Discovery Central is a Web portal and resource center for knowledge and information discovery from data. It encompasses areas such as Statistics, Data Mining, Knowledge Discovery in Databases, Machine Learning, Social Sciences, Marketing, and others.
Machine Learning Network Online Information Service - The MLnet OiS offers software, datasets, information about events, research groups, persons and other interesting stuff related to machine learning, knowledge discovery, case-based reasoning, knowledge acquisition, and data mining.
Online Machine Learning Resources - Provided by the ML Group at the Austrian Research Institute for Artificial Intelligence (OFAI).
Machine Learning at AAAI - Starting point for online machine learning resources. Provided by the American Association for Artificial Intelligence.
Kernel machines - A central information source for the area of Support Vector Machines, Gaussian Process prediction, Mathematical Programming with Kernels, Regularization Networks, Reproducing Kernel Hilbert Spaces, and related methods. Provides links to papers, upcoming events, datasets, code.
Computational Learning Theory - A research field devoted to studying the design and analysis of algorithms for making predictions about the future based on past experiences. The emphasis in COLT is on rigorous mathematical analysis. COLT is largely concerned with computational and data efficiency.
Reinforcement Learning Repository - A centralized resource for researchers of reinforcement learning. Maintained at Michigan State University.
Boosting research - A website on Boosting and related ensemble learning methods. Provided links to papers, upcoming events, datasets, code, etc
Mixture Modelling page - Mixture modelling, Clustering, Intrinsic classification, Unsupervised learning and Mixture modeling. Links and bibliography.
Gowachin - A competition on Grammatical Inference.
Reasoning about Computational Resource Allocation - An introduction to "anytime" algorithms. Published in Crossroads, the student magazine of the ACM.
Machine Learning in Games - How computers can learn to get better at playing games. This site is for artificial intelligence researchers and intrepid game programmers. I describe game programs and their workings; they rely on heuristic search algorithms, neural networks, genetic algorithms, temporal differences, and other methods.
Machine Learning FAQ - Questions and answers about Machine Learning. Anyone can post his/her own questions and answers.
ILPnet2 - Network of Excellence in Inductive Logic Programming.
David W. Aha: Machine Learning Page - Comprehensive machine learning resources from Applications to Tutorials.
Grammatical Inference - Repository of information on grammatical inference, automata induction, and language acquisition.
Pattern Recognition Information - A hub for Pattern Recognition linking to journals, books, bibliographies, jobs, conferences and news.
Machine learning for user modeling - Resources for researchers and practitioners interested in the use of learning techniques in intelligent, user-adaptive systems.
Programming by Example - Programming by example (or by demonstration) is a technique for teaching the computer new behavior by demonstrating actions on concrete examples. The system records user actions and generalizes a program that can be used in new examples.
Pattern Recognition Course - Links to various Pattern recognition and machine learning resources
Recursive-Partitioning.com -- Supervised & Unsupervised Learning - Recursive partitioning based supervised and unsupervised learning methods resources. Comprehensive lists of classification trees, regression trees, rules induction, and clustering software packages. Extensive bibliography collection. Links to machine learning and data mining websites.
Group Method of Data Handling (GMDH) - Review of the GMDH approach for data mining and forecasting, with examples and software
AI-CBR - Featured papers, researchers and projects, links to CBR people, research centres and projects, along with a comprehensive guide to software tools, a searchable online bibliography, virtual library, and a mailing list.
AAAI CBR Resources - Books, Proceedings, Electronic Resources, Mailing Lists/Newsletters, Web sites.
ML & CBR Folks - A list of home pages for people in machine learning and case-based reasoning.
Simon Fraser University CBR Group - Information about members and projects.
"Applying Case-Based Reasoning" - Contents of book by Ian Watson, on Morgan Kaufmann Publishers site. Can order online.
CADET - Case-based Design Tool - "System that aids conceptual design of electro-mechanical devices and is based on the paradigm of Case-based Reasoning." Project information, members, publications.
CBR: Foundational Issues, Methodological Variations, and System Approaches - "This paper gives an overview of the foundational issues related to case-based reasoning, describes some of the leading methodological approaches within the field, and exemplifies the current state through pointers to some systems." Published in 1994 in AICOM (Artificial Intelligence Communications).
Improving Accuracy by Combining Rule-based and Case-based Reasoning - Abstract for full paper, PDF full text available. "An architecture is presented for combining rule-based and case-based reasoning." Published in Artificial Intelligence in 1996.
CMU AI Repository: CBR Area - Direct link to CBR software and materials in the CMU AI repository.
Intro to CBR - Short intro includes information about technical issues, applications, suitability conditions, tools, and related websites and mailing lists.
CBR for Accumulating System Expertise - CBR is proposed as a basis to support recognition-primed decision making by system operators. A conceptual architecture that uses case-based reasoning as a source of control expertise is offered to support operations planning and automatic control. Published in 1995 Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics.
Imaging procedure selection and CBR - Abstract of paper about use of CBR in radiology (selecting diagnostic imagery techniques).
EWCBR94: References - List of authors and paper titles from the 2nd European Workshop on CBR (1994).
Creating User Interface Components by CBR - "helps a developer to select an application menu from a set of menus that are appropriate for the developer's project. It then inserts that menu directly into the developer's project. This paper uses CBR in creating user interface objects to achieve software reuse in a very effective and simple way." Published in CHI96.
Case-Based Reasoning: Experiences, Lessons, and Future Directions - Home page for the AAAI Press book, edited by David Leake. Includes the table of contents and a link to an on-line version of the chapter "CBR in Context: The Present and Future," a tutorial and overview of case-based reasoning research and applications.
Case-based Reasoning website of the IIIA - This is the website for all R&D work related to Case-based Reasoning (CBR) performed on the Institut d'Investigació en Intelligència Artificial (IIIA).
Nupedia: Case-Based Reasoning - An introductionary Encyclopedia article on Case-Based Reasoning written by a well known practitioner.
U-Mass CBR Group - Information about their research, publications, abstracts, and personnel.
ANGOSS Software Corporation - ANGOSS is a developer of advanced data mining software and solutions. They offer a comprehensive range of innovative, easy to use and affordable data mining solutions designed for business users - from the laptop through data warehouse environments to the Web. The products include KnowledgeSTUDIO and KnowledgeSEEKER.
Multi-EXPERT System Generation. - Multi-EXPERT System Generation, Rosetta-Stone Knowledge Engineering for Enterprise modeling and reengineering.
Making decisions based on terabyte database - The homepage of Attrasofts Decision Making systems.
RuleQuest Research Data Mining Tools - RuleQuest Research produces state-of-the-art knowledge discovery and data mining tools for Unix and Windows 95/98/NT/2000. These include See5 (decision trees) and Magnum Opus (association rules).
PharmaDM - A company specialized in customized scientific Data Mining tools and services for the pharmaceutical and biotechnology industry.
MLnet Mailing List - A moderated list, dedicated to the area of machine learning, knowledge discovery, case-based reasoning, knowledge acquisition, and data mining.
Machine Learning List - A moderated discussion list about Machine Learning. Email subscribe/unsubscribe request to ml-request@isle.org. Email contribution to ml@isle.org. It's sent out bi-monthly in digest format.
Support Vector Machine Mailing List - An unmoderated discussion list about Support Vector Machines methodology.
Recursive Partitioning Mailing List - An unmoderated mailing list for recursive partitioning based supervised learning methods, a.k.a. classification and regression trees.
Machine Learning Mailing List - An unmoderated mailing list intended for people in computer sciences, statistics, mathematics, and other areas or disciplines with interests in Machine Learning. Researchers, practitioners, and users of Machine Learning in academia, industry, and government are encouraged to join the list and participate.
ECML 2000 - European Conference on Machine Learning. Barcelona, Catalonia (Spain) May 30-June 2, 2000.
ICCBR 2001 - International Conference on Case-Based Reasoning Vancouver, British Columbia, Canada 30 July - 2 August 2001
ICML 1999 - The Sixteenth International Conference on Machine Learning. June 27-30, 1999, Bled, Slovenia.
ILP 1999 - The Ninth International Workshop on Inductive Logic Programming. June 24-27, 1999, Grand Hotel Toplice, Bled, Slovenia.
ICML 2001 - The Eighteenth International Conference on Machine Learning. Williams College (Massachusetts), June 28-July 1, 2001.
COLT 2001 and EuroCOLT 2001 - The Fourteenth Annual Conference on Computational Learning Theory (held jointly with the Fifth European Conference on Computational Learning Theory). Trippenhuis, Amsterdam, the Netherlands July 16 - July 19, 2001.
ECML and PKDD 2001 - 12th European Conference on Machine Learning (ECML'01) and 5th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'01).September 3-7, 2001, Freiburg, Germany.
ILP 2000 - The Tenth International Conference on Inductive Logic Programming. London, July 24-27, 2000.
ILP 2001 and LLL 2001 - The Eleventh International Conference on Inductive Logic Programming. Co-located with the Third International Workshop on Learning Language in Logic. Strasbourg, France, September 8-9, 2001.
ICML 2000 - Seventeenth International Conference on Machine Learning. Stanford University June 29-July 2, 2000.
AISTATS 2001 - Eighth International Workshop on Artificial Intelligence and Statistics. January 4-7, 2001, Hyatt Hotel, Key West, Florida
ALT 2001 - The Twelfth International Conference on Algorithmic Learning Theory. Washington D.C., November 25-28, 2001
ALT 2000 - The Eleventh International Conference on Algorithmic Learning Theory. Crowne Plaza Hotel (Coogee Holiday Inn), Sydney, Australia December 11-13, 2000
ALT 1999 - The Tenth International Conference on Algorithmic Learning Theory. Waseda University International Conference Center, Tokyo, Japan, December 6-8, 1999
IDA 2001 - The Fourth International Symposium on Intelligent Data Analysis. Cultural Centre of Cascais Lisbon, Portugal September 13-15, 2001
ICGI 2000 - 5th International Colloquium on Grammatical Inference. Instituto Superior Técnico - Lisbon, Portugal September 11-13th, 2000
COLT 2000 - Thirteenth Annual Conference on Computational Learning Theory, Stanford University. June 28 - July 1, 2000
ICML 1998 - The Fifteenth International Conference on Machine Learning. July 24-27, 1998 in Madison, Wisconsin.
UAI 2000 - The Sixteenth Conference on Uncertainty in Artificial Intelligence. Stanford University, June 30 - July 3, 2000.
AISTATS 1999 - The Seventh International Workshop on Artificial Intelligence and Statistics. Monday - Wednesday, January 4-6, 1999. Fort Lauderdale, Florida
ICCBR 1999 - The third International Conference on Case-Based Reasoning July 27 30, 1999. Monastery Seeon, Munich, Germany.
UM 2001 - The 8th International Conference on User Modeling. Sonthofen, Germany, July 13-17 2001.
MLDM 2001 - International Workshop on Machine Learning and Data Mining in Pattern Recognition. Leipzig, Germany, July 25-27, 2001.
IDEAL 2000 - Second International Conference on Intelligent Data Engineering and Automated Learning. December 13 - 15, 2000 The Chinese University of Hong Kong.
ACL 1999 Workshop: Unsupervised Learning in Natural Language Processing - Workshop at the 37th Annual Meeting of the Association for Computational Linguistics. University of Maryland, June 21, 1999.
CoNLL 2001 - Computational Natural Language Learning (CoNLL) 2001. A workshop at the Annual Meeting of the Association for Computational Linguistics. University of Social Sciences, Toulouse, France, July 6, 2001.
CONALD 98 - Conference on Automated Learning and Discovery. Carnegie Mellon University, June 11-13 1998.
UAI 2001 - The Seventeenth Conference on Uncertainty in Artificial Intelligence. University of Washington, Seattle, August 2-5, 2001.
Machine Learning and Inference Laboratory - GMU - Research on Theories of Learning, Inference, and Discovery Data Mining and Knowledge Discovery, User Modeling and Intrusion Detection, Non-Darwinian Evolutionary Computation, Machine Vision through Learning, Education.
Machine Learning Group - UCI - Research at UCI spans the spectrum of models for learning, including those based on statistics, logic, mathematics, neural structures, information theory, and heuristic search algorithms.
Machine Learning Group - University of Waikato - Offers WEKA, a comprehensive, open-source (GPL) machine learning and data mining toolkit in Java with classification, regression, clustering, and association rules. Command-line and GUI interfaces.
Artificial Intelligence Research Laboratory - Iowa State University - Resarch related to machine learning includes neural networks, automata induction, computational learning theory, data mining, knowledge discovery, bioinformatics.
Cognitive Computation, Harvard University - The group develops theories and systems pertaining to intelligent behavior using a unified methodology. At the heart of the approach is the idea that learning has a central role in intelligence.
Intelligent Data Analysis Group at GMD FIRST - The IDA group is concerned with learning systems for intelligent data analysis. In particular, we are developing tools for high-dimensional multivariate statistics based on methods originally developed in the field of statistics and, more recently, in the neural networks and machine learning community.
Cognitive Computation Group at UIUC - Developing theories and systems pertaining to intelligent behavior using a unified methodology. At the heart of the approach is the idea that learning has a central role in intelligence.
Machine learning and Neural Networks group - Universities of Florence, Pisa, and Siena - Research on adaptive processing of data structures, document analysis and technologies, natural language, machine learning for the web, visual databases, biochemistry and bioinformatics.
Machine Learning and Natural Language Processing Lab - Freiburg (Germany) - Research on Data Mining, Machine Learning,Inductive Logic Programming, Relational Learning, Machine Learning for Bioinformatics.
Machine Learning - ÖFAI - Information on their members, research areas, publications, teaching, and resources. Focus is on: data mining and knowledge discovery in databases, inductive logic programming, knowledge intensive learning, concept drift and context-sensitive learning, minimum description length principle, machine learning and music.
Computational Intelligence Group - University of Bristol - Research on kernel methods, support vector machines, neural networks, machine vision, bioinformatics, computational learning theory.
Machine Learning Research Group - UTCS - Research on General Inductive Learning, Inductive Logic Programming, Natural Language Learning, Qualitative Modeling & Diagnosis, Learning for Planning and Problem Solving. Recommender Systems and Text Categorization Student Modeling for Intelligent Tutoring Systems Text Data Mining Theory and Knowledge Refinement.
Learning Lab at CMU, School of Computer Science - Software systems that learn user preferences, Robot learning, text learning, generic learning methods.
Machine Learning Research Group - UW-Madison - Research on information retrieval and extraction, bioinformatics, connectionist models, hybrid systems.
Machine Learning and Genetic Algorithms group - University of Turin - Research on learning first-order classification rules, first-order concept descriptions, genetic algorithms, neural networks, computational learning theory.
Institute for Process Control and Robotics - University of Karlsruhe (Germany) - Research on Machine Learning in Robotics, Factory Automation, and Assistance Systems.
Machine Learning Lab - The Hebrew University - Research projects on learning in human-machine interaction, natural language interface to the WWW, statistical analysis of neurophysiological data, self-organization of proteins, nonlinear acoustic signal processing.
Centre for Learning Systems and Applications (LSA) - University of Kaiserslautern (Germany) - Research on Machine Learning, Case-based Reasoning, Knowledge Acquisition
IDIAP machine Learning Group - Martigny (Switzerland) - Research on Support Vector Machines, Hidden Markov Models, fusion of generative and discriminative approaches, logical data analysis, large scale data analysis.
Gatsby Computational Neuroscience Unit - University College London - Research on neural computational theories of perception and action, with an emphasis on learning.
The Auton Project - Research on Data Mining, Active Learning & Exploration, Reinforcement Learning for Decision and Control.
Machine Learning at UC Santa Cruz - Research on decision theory, neural networks, computational biology, computational geometry, theoretical computer science, on-line learning algorithms, computational learning theory, reinforcement learning.
LISA - Adaptive Computer Systems Laboratory - Université de Montréal - Research on modeling high-dimensional data, learning hyper-parameters, boosting of neural networks, Markovian models, data mining, and other areas related to neural networks.
Machine Learning Laboratory - UMass - Research on Neural Networks and Decision Trees.
Robot Learning Laboratory - CMU - Research on Localization and Mapping, Partially Observable Markov Decision Processes, Computer Vision and Image Processing, Robot Architectures and Programming Languages, Learning Algorithms.
Knowledge Acquisition & Machine Learning Lab - University of Bari - Research on symbolic and numerical approaches to machine learning, first order logic, intelligent document processing, spatial data mining, human-computer interaction.
Machine Learning Group - Stockholm University - Research on inductive logic programming for natural language processing and for knowledge discovery in databases.
Computational Learning - Royal Holloway, University of London - Research on machine learning theory, kernel methods for text analysis, support vector machines, kernel theory.
Center for Automated Learning and Discovery - CMU - Large group with projects in robot learning, data mining for manifacturing and in multimedia databases, causal inference, disclosure limitation, World Wide Web.
Machine Learning Research Group of Rutgers University - Research interest in online algorithms, sequence categorization, action prediction, genetic algorithms, and feature generation/selection.
Machine Learning at the Katholieke Universiteit Leuven - Research in Data mining, Inductive Logic Programming, Learning In Agents.
Center for Biological and Computational Learning - MIT - Research on theory of learning, neuroscience, bioinformatics & functional genomics, information extraction in text & multimedia, object detection/recognition, man-machines interfaces, virtual financial markets.
AI Unit - University of Dortmund (Germany) - Research on representation and acquisition of knowledge in the subareas machine learning and text, knowledge discovery in databases, learning and cognitive science, and learning robots.
Machine Learning Group - University of Bristol - Research on higher-order concept learning, inductive logic programming, multi-agent learning systems, integration of prior knowledge, induction and deduction, incremental learning, hybrid symbolic/connectionist approaches, evolutionary strategies.
Knowledge Acquisition and Machine Learning Group - University of Ottawa - Research projects mainly focused on text: Intelligent Information Access, Text Summarization, Text Analysis for Knowledge Acquisition.
The Machine Learning Systems Group at JPL - Applied research in data mining, knowledge discovery, pattern recognition, and automated classification and clustering.
Automated Learning Group - NASA - Research projects on collective intelligence, surface modeling, autoclass, Bayesian search.
Computational Biology Group - University of Wales - Techniques include inductive logic programming, model based reasoning, evolutionary computing, neural networks, multivariate statistics. Applications to drig design, protein secondary structure prediction, functional genomics, etc.
Bioinformatics and Learning Metrics group - Helsinki University of Technology - Analysis of functional genomics data, Construction of data-dependent metrics for focusing data analysis on relevant or important aspects of the data.
The BUGS Project - Bayesian inference Using Gibbs Sampling - BUGS is a piece of computer software for the Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods. Software for several platforms is available for downloading, and all the manuals are also available online or in downloadable formats.
MLC++ - MLC++ is a library of C++ classes for supervised machine learning. Provided by SGI. [Free for internal research purposes]
An AI learning system - A description of an AI system, with a demonstration program and Delphi sourcecode available.
LIBSVM - A Library for Support Vector Machines - LIBSVM is an integrated tool implementing support vector classification, regression, and distribution estimation. C++ and Java sources available. [Free]
The `Bow' Toolkit for statistical language modeling, text retrieval, classification, and clustering - Bow (or libbow) is 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]
AutoClass - AutoClass takes 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]
WinMine Toolkit - Tools for learning dependency networks or Bayesian networks from data. [Free]
Bayes Net Toolbox for Matlab - Supports several inference algorithms (e.g. junction tree, Pearl, variable elimination etc.) and learning algorithms (e.g. EM, MCMC, structure learning, etc). Allows simulation of static and dynamic networks, including HMMs, IOHMMs, and Kalman filters.
Software Packages for Graphical Models / Bayesian Networks - A list of software packages for Graphical Models / Bayesian Networks. Some have learning capabilities.
FastMix - FastMix generates Gaussian mixture models for large datasets using efficient EM clustering algorithms. [Free]
Incremental Decision Tree Induction - An algorithm that incrementally constructs decision trees from labeled examples. [Free for individual research purposes]
C4.5 and FOIL - Home page of R. Quinlan. FTP links to FOIL (inductive logic programming) and C4.5 (learning decision trees).
Weka 3 - Open Source Machine Learning Software in Java - Suite that implements decision trees and tables, rule learners, Naive Bayes, support vector machines, voted perceptrons, multi-layer perceptron. Meta schemes include bagging, stacking, boosting etc. [Free under GPL]
The NEITHER Theory Revision System - 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]
LNKnet Pattern Classification Software - LNKnet is 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]
PRODIGY system - An architecture for planning and learning. [Free]
HMMER - Profile hidden Markov models for biological sequence analysis - Sean Eddy's tools to build HMMs from multiple alignments, align sequences to HMMs, calculate e-scores, and other tools.
The R Project for Statistical Computing - 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, clustering, etc.).
Machine Learning Packages from the CMU Artificial Intelligence Repository - Links to external ftp sites. Systems include ACCEL, CLASSWEB, FOCL, FOIL, GOLEM, INDEX, MILES, MOBAL, OC1, Occamn, PEBLS, RWM
The CHILL empirical parser acquisition system - CHILL is 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]
TiMBL: Tilburg Memory Based Learner - TiMBL is 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). [Free for educational or non-commercial research purposes]
Meta-MEME v2.0.1 - Software toolkit for building and using motif-based hidden Markov models of DNA and proteins - from the Univ. of California-San Diego.
SUBDUE: Knowledge Discovery in Structural Databases - The program discovers interesting and repetitive subgraphs in a labeled graph representation using the minimum description length principle. Applications to molecular biology. [Free]
SNoW - SNoW is a learning architecture specifically taylored for learning in very high-dimensional feature spaces. The current release uses sparse variations of Winnow, Perceptron, and Naive Bayes. [free for personal academic and research purposes]
HMM and other statistical programs - 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.
BETSY - Bayesian Essay Test Scoring sYstem - BETSY is a freeware windows-based program that classifies text based on trained material. Designed for automated essay scoring, BETSY can be applied to any text classification task.
Pfam - A large collection of multiple sequence alignments and trained hidden Markov models covering many common protein domains.
The MEME/MAST system - MEME (Multiple EM for Motif Elicitation) is a program for discovering motifs (highly conserved regions) in groups of related DNA or protein sequences. MAST (Motif Alignment and Search Tool) is a tool for searching biological sequence databases for sequences that contain one or more of a group of known motifs.
SAM: Sequence Alignment and Modeling System - SAM is a collection of tools for creating and using HMMs for biological sequences. Free license for academic and nonprofit usages.
EM algorithm for Mixture models - Shotaro Akaho implementation of EM algorithm for modeling Mixtures of Gaussians (in Java). Free. An extended version is available from the author.
MIX - Software for learning Mixture Distributions. Commercial license.
Machine learning programs by Peter Clark - QM: Guiding inductive learning with a Qualitative Model. LPE: Lazy Partial Evaluation. CN2: Rule induction from examples. Free.
Statistical Decision Trees - A program for inducing Bayesian decision trees. Applications to speech. [Free]
SVM-Light: Support Vector Machine Software - Training software for large-scale SVMs. [Free for non-commercial use]
RISE: Repository of Information Sources used in information Extraction tasks. - Repository of online information sources: test domains for information extraction and wrapper generation tools that learn extraction rules (extraction patterns).
The RCSB Protein Data Bank (PDB) - Archive of experimentally-determined, biological macromolecule 3-D structures from the Brookhaven National Laboratory.
Dataset generator - Datgen, formerly SCDS, is a computer program that generates data to systematically test programs that consume data. These synthetic datasets can be used to validate learning algorithms.
Bilkent University Function Approximation Repository - Datasets used for the experimental analysis of function approximation techniques and for training and demonstration by machine learning and statistics community.
DELVE - Data for Evaluating Learning in Valid Experiments - Data for Evaluating Learning Valid Experiments: A standardized environment designed to evaluate the performance of methods that learn relationships based primarily on empirical data. Delve makes it possible for users to compare their learning methods with other methods on many datasets.
UCI Machine Learning Repository - 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.
TREC Data - Text datasets used in information retrieval and learning in text domains.
National Space Science Data Center - Provides access to a wide variety of astrophysics, space physics, solar physics, lunar and planetary data from NASA space flight missions, in addition to selected other data and some models and software.
The StatLib Datasets Archive - A repository of datasets used in statistics and machine learning.
NIST Special Database 4. - This NIST database of fingerprint images contains 2000 8- bit gray scale fingerprint image pairs.
Face recognition dataset - A dataset of face images for face recognition algorithms.
DNA microarray gene expression data - A collection of public gene expression data sources maintained by A. Brazma.
Time Series Data Library - A collection of over 500 time series, maintained by Rob Hyndman. Time series are organized by subject.
Penn Treebank Project - A corpus of parsed sentences. Used by many researchers for training data-driven parsing algorithms.
University of Maryland, INFORUM EconData - Several hundred thousand economic time series, produced by the U.S. Government and distributed by the government in a variety of formats and media, have been put into a standard, highly efficient, easy-to- use form for personal computers.
HS3D - Homo Sapiens Splice Sites Dataset - HS3D (Homo Sapiens Splice Sites Dataset) is a database of Homo Sapiens Exon, Intron and Splice regions extracted from GenBank primate sequences Rel.123. The aim of this data set is to give standardized material to train and to assess the prediction accuracy of computational approaches for gene identification and characterization.
Learning Relational Concepts from Sensor Data of a Mobile Robot - A set of data sets, where each data set is represented in first order logic. Maintained at the University of Dortmund, Germany.
AdEater data - AdEater is a program that learns to remove Internet advertisements. The machine learning dataset is available from this page.
The 20 Newsgroups Data Set - 20 Newsgroups for text categorization. Widely used dataset.
Web->KB dataset - Web pages partitioned into classes, with hyperlink data. The dataset has been used for text categorization and learning to extract symbolic knowledge from the World Wide Web.
WordSimilarity-353 Test Collection - Contains 353 English word pairs along with human-assigned similarity judgements.
Machine Learning on Non-Homogeneous, Distributed Text Data - PhD thesis: Dunja Mladenic, University of Ljubljana, Slovenia. An approach to automatic document categorization based on a large categorization hierarchy is proposed.
Applying a Machine Learning Workbench: Experience with Agricultural Databases - By Stephen R. Garner, Sally Jo Cunningham, Geoffrey Holmes, Craig G. Nevill-Manning, and Ian H. Witten. (1995). [PDF]
Machine Learning Journal - An international journal on computational approaches to learning. Online access available with subscription.
IEEE Transactions on Knowledge and Data Engineering - Focus is maily on data and knowledge management systems, and Artificial Intelligence. Some papers and special issues are related to data mining and machine learning.
IEEE Transactions on Pattern Analysis and Machine Intelligence - The journal focuses on pattern recognition and related areas including vision, feature extraction, knowledge representation, logical and probabilistic inference, learning, speech recognition, character and text recognition.
Journal of Artificial Intelligence Research - An electronic scientific journal covering all areas of artificial intelligence (AI), publishing refereed research articles, survey articles, and technical notes.
Journal of Machine Learning Research, Homepage - Provides an international forum for the electronic and paper publication of high-quality scholarly articles in all areas of machine learning. Final versions are published electronically immediately upon receipt, and an annual paper volume is published and sold to libraries and individuals.
Bibliography of EuroCOLT - European Conference on Computational Learning Theory. Since 1993. Maintained by DBLP at University of Trier.
Biblioghaphy of ICML - International Conference on Machine Learning. Since 1988. Maintained by DBLP at University of Trier.
Bibliography of ALT - Annual Algorithmic Learning Theory conference. Since 1990. Maintained by DBLP at University of Trier.
Bibliography of COLT - Computational Learing Theory. Since 1988. Maintained by DBLP at University of Trier.
Bibliography of ECML - European Conference on Machine Learning. Since 1987. Maintained by DBLP at University of Trier.
Bibliography of MLDM - Workshop on Machine Learning and Data Mining in Pattern Recognition. Since 1999. Maintained by DBLP at University of Trier.
Bibliography of SOM papers - A collection of works that have been based on the Self-Organizing Map (SOM) method developed by Kohonen
Bibliography on Automated Text Categorization - Maintained by F. Sebastiani. About 200 online publications and 300 references.
Warren S. Sarle's Bibliography on Cluster Analysis - Useful clustering literature collected by Warren S. Sarle and originally published in the SAS/STAT User's Guide (1990)
T.S. Lim's Bibliography on Tree-Structured Methods - Books, journal articles, conference proceedings, technical reports related to classification & regression trees
Bioinformatics: The machine learning approach - by P. Baldi and S. Brunak, MIT Press February 1998.
Support Vector Machines, Neural Networks and Fuzzy Logic Models - A textbook that provides a thorough, comprehensive and unified introduction to the field of learning from experimental data and soft computing.
Introduction to Machine Learning - By Nils J. Nilsson (downloadable draft)
Machine Learning, Neural and Statistical Classification - This book is based on the EC (ESPRIT) project StatLog which compare and evaluated a range of classification techniques, with an assessment of their merits, disadvantages and range of application. This integrated volume provides a concise introduction to each method, and reviews comparative trials in large-scale commercial and industrial problems. It makes accessible to a wide range of workers the complex issue of classification as approached through machine learning, statistics and neural networks, encouraging a cross-fertilization between these discplines.
An Introduction to Support Vector Machines - First comprehensive introductory book to the field of Support Vector Machines, a novel machine learning algorithm.
Machine Learning textbook - A textbook by Tom Mitchell, McGraw Hill, 1997.
Reinforcement Learning: An Introduction - by Sutton & Barto, MIT Press, 1998.
Computational Methods in Molecular Biology - Edited by S. Salzberg, D. Searls, and S. Kasif. Elsevier Science, 1998. The book is largely devoted to machine learning approaches to molecular biology. The site includes an online appendix.
Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. - by R. Durbin, S.R. Eddy, A. Krogh, G.J. Mitchison. Focus is mainly on machine learning methods for alignment, phylogeny, and RNA structure analysis.
Repository of papers on Machine Learning and Information Retrieval - A collection of online papers about ML approaches to Information Retrieval. Maintained by R. Belew and J. Shavlik.

netmation.com | netmation.net | netmation.org | netmation.tv

Netmation

Software

Reference

Help