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This implements a phrased-based hidden semi-Markov Model for SMT
This package implements the phrased-based hidden semi-Markov model described:
Jesús Andrés-Ferrer, Alfons Juan. A phrase-based hidden semi-Markov approach to machine translation. Procedings of European Association for Machine Translation (EAMT), 2009. pp. 168-175.
This project depends on jaf_Utils:
http://sourceforge.net/projects/jafutils/
Install it prior installation of jaf_MT.
An artificial neural network, currently specialized to save a specific bit pattern, mainly by changing the signal propagation delays in links. More features, variables and algorithms will be added in time.
Similarity Word-Sequence Kernels for Sentence Clustering toolkit
This project implements the techniques used in this paper:
@INPROCEEDINGS{Andres10a,
author = {Jesús Andrés-Ferrer and Germán Sanchis-Trilles and Francisco Casacuberta},
title = {Similarity Word-Sequence Kernels for Sentence Clustering},
booktitle = {Proceedings of the 8th International Workshop on Statistical Pattern Recognition},
year = {2010},
}
This project depends on jaf_Utils:
http://sourceforge.net/projects/jafutils/
Install it prior...
This project contains weka packages of neural networks algorithms implementations like Learning Vector Quantizer (LVQ) and Self-organizing Maps (SOM). For more information about weka, please visit http://www.cs.waikato.ac.nz/~ml/weka/
This Java software implements Profile Hidden Markov Models (PHMMs) for protein classification for the WEKA workbench. Standard PHMMs and newly introduced binary PHMMs are used. In addition the software allows propositionalisation of PHMMs.
3-layer neural network for regression and classification with sigmoid activation function and command line interface similar to LibSVM.
Quick Start: "java -jar nen.jar"
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.
This is a RapidMiner extension replacing the current Weka-Plugin with the updated 3.7.3 Weka-Version. This is basically a branch of the 3.7.3 Version of WEKA wrapped into the old extension. New Features Include:
-All the Features of the 3.7.3 Weka Package
-Multi-Threaded ensemble learning
-An enhancement on the popular RandomForest Learner based on "Dynamic Integration with Random Forests" by Tsymbal et al. 2006 and "Improving Random Forests" by Robnik-Sikonja 2004.
-More enhancements...
This project is devoted to the creation of an open source Error-Correcting Output Codes (ECOC) library for the Machine Learning community. The ECOC framework is a powerful tool to deal with multi-class categorization problems.
DOGMA is a MATLAB toolbox for discriminative online learning. It implements all the state of the art algorithms in a unique and simple framework. Examples are Perceptron, Passive-Aggresive, ALMA, NORMA, SILK, Projectron, RBP, Banditron, etc.
This RapidMiner-plugin consists of operators for feature selection and classification - mainly on high-dimensional (microarray-) data - and some helper-classes/operators.
RobGP is a genetic programming system written from the ground up in C++. It's primary goals are efficiency, ease of use, and extensibility. It's distinguishing feature is that it has a modified version of Koza's architecture altering operations.
The Mars Rover Simulator project is based on the evolutionary robotics paradigm where an artificial agent acquires its skills through the process of artificial evolution. This simulator can be useful to evolve neural network controllers for the rover
Feating constructs a classification ensemble comprising a set of local models. It is effective at reducing the error of both stable and unstable learners, including SVM. For details see the paper at http://dx.doi.org/10.1007/s10994-010-5224-5.
Leark is a Data Mining library developed in C#.NET. It contains several methods for ranking web documents described with a set of normalized features, and a feature selection algorithm. The methods are based on perceptron and clustering.
RoboBeans is an interface to the "Robocup 2D Soccer Simulation Server" that allows developers to write Robocup teams\agents concentrating on behaviour and AI without having to worry about syntax of communication or network issues.
The aim of ALIVE is to develop new approaches to the engineering of flexible, adaptable distributed service-oriented systems based on the adaptation of social coordination and organisation mechanisms.
The data complexity library, DCoL, is a machine learning software that implements all metrics to characterize the apparent complexity of classification problems. The code is implemented in C++ and can be run on multiple platforms.