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A discretization algorithm based on the Minimum Description Length. Implemented as a filter according to the standards and interfaces of WEKA, the Java API for Machine Learning. More Info: http://bruno-wp.blogspot.com/search/label/Software
Proposed is an algorithm
that uses computer vision, combined with a modified Rubine classifier, to allow
arbitrary N-sided polygons as accepted sketches in real-time.
Random Forest classification implementation in Java based on Breiman's algorithm (2001). It assumes the data is in the form [ X_1, X_2, . . ., X_M, Y ] where Y \in {0, 1, . . ., C}. The user must define M, C, and m initially.
Wodka is the implementation of a genetic algorithm (GA) that can bread two dimensional structures that might be used as robots in sodarace competitions.
RL HNFP is a neuro Fuzzy model which can automatic generate set of rule. So it can implement in domain although human don't have knowledge on it. This project implement that algorithm in Java so other people can use that for their application
The project implements Dana Angluin's learning algorithm with intent to look into the possibility of computational learning of changing (shifting) information.
DrPangloss is a python implementation of a three operator genetic algorithm, complete with a java swing GUI for running the GA and visualising performance, generation by generation
KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
AI-based, Comprehensive Service Management for Businesses and IT Providers
Modular solutions for change management, asset management and more
ChangeGear provides IT staff with the functions required to manage everything from ticketing to incident, change and asset management and more. ChangeGear includes a virtual agent, self-service portals and AI-based features to support analyst and end user productivity.
This project intends to create an indexing search engine, for knowledge management. The primary object is to apply an information retrieval core. And implement a knowledge data discovery theory such as data mining algorithm, text mining.
A Java implementation of the NEAT algorithm as created by Kenneth O Stanley. Also provides a toolkit for further experiments to be created and can provide both local and distributed learning environments.
musicomp is a program which most important element is an evolutionary algorithm which uses data mining methods as a fitness function to generate monophone melodies.
In imitative learning, an agent will attempt to match what is observed to their memory. By visualizing the incorrectly matches "scenes", this project will allow algorithm developers to gain a better understanding of what causes their algorithms to fail.
It is an universal language translator and written in Java. All languages are translated to an unique language (interlingua) and generate any native language from the interlingua. The wordbooks are XML. It use the context of a text, rules and a grammar.
ANJI
(Another NEAT Java Implementation)
Built on top of existing OpenSource projects, ANJI is an implementation of NEAT (Neuro-Evolution of Augmenting Topologies), an algorithm for evolving artificial neural networks.
A flexible Japanese to English language translation engine that allows multiple results be displayed according to all possible grammar ratings, i.e. a list of results will be displayed instead of only one. Please browse the CVS tree for actual project.
EasyAI is a project to build classical AI program and method in Java language, such as resolution for logic, greedy search, genetic algorithm, neural network and so on...
IslandEv distributes a Genetic Algorithm (like <a href="/projects/jaga">JaGa</a>) across a network (see <a href="/projects/distrit">DistrIT</a>) using an island based coevolutionary model in which neighbouring islands swap migrating individuals every
Gazoo is a Java framework for genetic algorithms development. Gazoo provides the core of a genetic algorithm, leaving to the user the implementation of specific-problem classes.
Solving the travelling salesman problem with genetic (evolutionary) algorithms. The distance calculations are based on geographical coordinates. The progress of the algorithm is visualized with a geo-map and some statistics.
Tired of spending hours of sleep tuning you Robocode Bot?
Your bot is full of constants that if wrong tuned would let to awfull performances?
BotOptimizer will help you tune the bot, allowing you to define also your optimization algorithm.