Search Results for "learning classifier system"

Unitag is a language-independent Unicode-based part-of-speech tagging system. Written entirely in ANSI-compatible C, it should (in theory) compile on any OS, but has been tested on 32-bit Windows.

Linux kernel fork-off with cloud and machine learning features

This project is a rewritten of an initial project that I've called GLUE and created in 2005. I'm trying to readapt it for Python 2.7.3 and GCC 4.6.3 The library has to be build as a simple Python extension using >python setup.py install and allows to create different kind of servers, clients or hybryds (clients-servers) over (TCP/UDP) using the Ipv6 Protocol. The architecture of the code is based on brain architecture. Will put an IPv6 adress active available as soon as...

Lens is the light, efficient network simulator, written by Doug Rohde. LensOSX is a native MacOSX port of Lens that runs on MacOSX 10.5 or higher, created by Harm Brouwer, Daniel de Kok and Hartmut Fitz.

BNNS is a research tool for interactive training of artificial neural networks based on the Response Function Plots visualization method. It enables users to simulate, visualize and interact in the learning process of a Multi-Layer Perceptron on tasks which have a 2D character. Tasks like the famous two-spirals task or classification of satellite image data.

TexLexAn is an open source text analyser for Linux, able to estimate the readability and reading time, to classify and summarize texts. It has some learning abilities and accepts html, doc, pdf, ppt, odt and txt documents. Written in C and Python.

An open source system for supervised document classification based on statistical machine learning techniques. On the contrary of the state of art classification techniques, MyNook just requires the title of the document, not the content itself.

This is a very elementary GP system written in C/C++ of symbolic regression,The input to the program is the file containing Terminal set.

The intention of this project is to give all serious users of the SNNS a place where they find a bugfix and patch management and where they get useful information about the SNNS.

MoMS (Model Management System) is a model management system for statistical models, a little bit like a database management system. Instead of having tables, we have models that can be updated and queried.

Weekend-robotics enables the dedicated amateur to build a autonomous robot. It runs on a Linux system for high-level operations and offers an interface to the defacto standard hardware abstraction layer in robotics, Player/Stage.

A packet dissector driven by machine learning algorithms. You train it to recognize specific types of packets by showing it examples and counterexamples of some packet type, and it will figure out which bits in the packet define it as the type you seek.

A fast kernel density estimation based classifier. Uses multi resolution KD trees to significantly reduce the number of calculations needed to perform density estimation.

a distributed engine for abstract neural network development via natural-language programming