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A packet dissector driven by machinelearning 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.
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A C++ library for machinelearning within dynamic systems. It provides methods such as the Kalman, unscented Kalman, and particle filters and smoothers, as well as useful classes such as common probability distributions and stochastic processes.
This project is developing a modular framework for constructing machine intelligences. The modular approach allows for both rapid development of simple AI's and also construction of larger and more general learning based engines.
Structlab is a machinelearning 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.
Dataset Retrieval through Intelligent Agents (DARIA): is an Open Source project for facilitating the construction of ARFF data set files for use with WEKA or any such MachineLearning/Data Mining Software through the use of Intelligent Agents.
T-Rex (Trainable Relation Extraction) is a highly configurable machinelearning-based Information Extraction from Text framework, which includes tools for document classification, entity extraction and relation extraction.
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TimeSleuth discovers temporal decision rules. It also judges the (a)causality of the rules. TimeSleuth can discover rules that involve time: {if (rainy_yesterday = true) then rainy_today = true}, or {if (rainy_tomorrow = true) then rainy_today = true}.
COLDIC is an integrated lexicographic platform for creation and management of electronic lexica. Generates itself automatically from a DTD with the database schema and provides human interfaces (query and insert tools) and machine interfaces(webservices)
Cerberus is a First Person Shooter Game that incorporates machinelearning techniques. The game utilizes Neural Networks to control fighting behavior and Reinforcement Learning to select high level tactics.
The simpleSVM project contains MachineLearning codes for algorithms based on the SimpleSVM. It provides methods for Support Vector Machines and related methods, such as One-Clas SVM, nu-SVM...
PIQLE is a Platform Implementing Q-LEarning (and other Reinforcement Learning) algorithms in JAVA. Version 2 is a major refactoring. The core data structures and algorithms are in piqle-coreVersion2. Examples are in piqle-examplesVersion2. A complete doc
Zabal6 is a machinelearning student tool based on decision tree learning, focused in the area of knowledge discovery (data mining), and inspired on See5. Zabl6 is a C++ program for Linux and windows O.S, with a intuitive graphical interface.
The Decision Tree Learning algorithm ID3 extended with pre-pruning for WEKA, the free open-source Java API for MachineLearning. It achieves better accuracy than WEKA's ID3, which lacks pre-pruning.Info: http://bruno-wp.blogspot.com/search/label/Softwar
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 MachineLearning. More Info: http://bruno-wp.blogspot.com/search/label/Software
Machinelearning toolkit for unsupervised and semi-supervised clustering that demonstrates excellent results on real-world data (see Bekkerman et al. ICML-2005 and ECML-2006).
Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machinelearning problems and a specific set of models for gene prediction using semi-Markov CRFs.
A tool for segmenting objects of interest in images, namely creating masks, and storing them for a set of images. It may provide some automatic/interactive segmentation for certain classes of objects. For computer vision / machinelearning applications.
KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machinelearning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
PCP (Pattern Classification Program) is an open-source machinelearning program for supervised classification of patterns. PCP is a binary executable running on Linux and Windows (under Cygwin environment).
An object-oriented platform and algorithms for the game of GO.
Aims:
1) A capable engine that can learn through experience.
2) A re-usable algorithmic framework for rapid development of new
GO-playing engines.
MultiBoost is a C++ implementation of the multi-class AdaBoost algorithm. AdaBoost is a powerful meta-learning algorithm commonly used in machinelearning. The code is well documented and easy to extend, especially for adding new weak learners.