Search Results for "learning classifier system"
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Showing 14 open source projects for "learning classifier system"
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Conscious Artificial Intelligence
It's possible for machines to become self-aware.
This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses. This project has 2 subprojects: Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api A video from the first prototype has been made: http://www.youtube.com/watch?v=qH-IQgYy9zg Above video shows a popperian agent collecting mining ore from 3... -
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TEES
Turku Event Extraction System
Turku Event Extraction System (TEES) is a free and open source natural language processing system developed for the extraction of events and relations from biomedical text. It is written mostly in Python, and should work in generic Unix/Linux environments. Currently, the TEES source code repository still remains on GitHub at http://jbjorne.github.com/TEES/ where there is also a wiki with more information. -
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MCCCS
Multi Channel Classification and Clustering
Here we present an image-based Multi Channel Classification and Clustering System (MCCCS). It is an generalized, script-based classification system for processing various kinds of image data. Due to the modular design, individual processing-components can be easily adapted, extended or exchanged by own extensions. See project website for installation instructions. -
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ExSTraCS
Extended Supervised Tracking and Classifying System
This advanced machine learning algorithm is a Michigan-style learning classifier system (LCS) developed to specialize in classification, prediction, data mining, and knowledge discovery tasks. Michigan-style LCS algorithms constitute a unique class of algorithms that distribute learned patterns over a collaborative population of of individually interpretable IF:THEN rules, allowing them to flexibly and effectively describe complex and diverse problem spaces. ... -
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FingerID
Metabolite identification via machine learning.
[NOTICE!] FingerID since version 1.4 will be hosted on github: https://github.com/icdishb/fingerid A metabolite identification software using tandem mass spectrometry and kernel methods. The related paper can be found at http://bioinformatics.oxfordjournals.org/content/early/2012/07/18/bioinformatics.bts437.abstract. Now it supports unix/linux like system. -
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EducationalLCS
eLCS - Educational Learning Classifier System
Educational Learning Classifier System (eLCS) is a set of learning classifier system (LCS) educational demos designed to introduce students or researchers to the basics of a modern Michigan-style LCS algorithm. This eLCS package includes 5 different implementations of a basic LCS algorithm, as part of a 6 stage set of demos that will be paired with the first introductory LCS textbook. -
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A base for programs. Includes algorythms for Q-learning and SOM's etc. too. Examples: Hamron: Simulates evolution, uses the 2D-renderer. DriveUnit: created for school, for a robotic arm, uses the 3D-renderer. Hlearn: http://www.sagenb.org/home/pub/8
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CRUMp
A probabilistic prediction system of protein phosphorylation sites
CRUMp is based on a kernel-based learning method called Classification Relevance Units Machine (CRUM). Given an input set of protein sequences in FASTA format, the system outputs the position, residue type (S, T, or Y), and the estimated probability of each tested site being phosphorylatable. Latest downloadable files: - crump-0.2.0.tar.gz: CRUMp GNU Octave package - crump-0.2.0.zip: CRUMp MATLAB script - crumptestset.fasta: A testing dataset in FASTA format. -
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Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.
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GLEAN is an unsupervised learning system to integrate disparate sources of gene structure evidence (gene model predictions, EST/protein genomic sequence alignments, SAGE/peptide tags, etc) to produce a consensus gene prediction, without prior training.
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This project develops a web-based (JSP) Fuzzy Rule-Based Expert System for analyzing ECG (electro cardio gram) signals & diagnosing Tachi-Arrhythmias. Proj. main blocks: inference engine, knowledgebase, KB editor, explanation, and feature extraction.
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Structlab is a machine learning C++ framework for structured domains, which provides a toolbox of learning methods and tools for preprocessing and visualization. It also provides a GUI to setup elaborate experiments in a visual and intuitive way.
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CompLearn is a general-purpose compression-based machine learning system that uses data compression to learn or data mine patterns in arbitrary data.
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iMate is a win32 / Linux desktop mate programme. It offers more features than the already existing desktop mate (AI, learning capacity, growth and limited lifeTime, third party tools to add new behaviour, ...).
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