Projects

MALLET

MALLET (A Machine Learning for Language Toolkit) is an integrated collection of Java code useful for statistical natural language processing, document classification, clustering, information extraction, and other machine learning applications to text

randomforest-matlab

This is a Matlab (and Standalone application) port for the excellent machine learning algorithm `Random Forests' - By Leo Breiman et al. from the R-source by Andy Liaw et al. http://cran.r-project.org/web/packages/randomForest/index.html ( Fortran original by Leo Breiman and Adele Cutler, R port ... [More] by Andy Liaw and Matthew Wiener.) Current code version is based on 4.5-29 from source of randomForest package. I especially am grateful for all the help i got from Andy Liaw. This project would not have been possible if not for the previous code by Andy Liaw, Matthew Wiener, Leo Brieman, Adele Cutler. The wiki has short articles on using rfImpute to input in missing values and basic installation procedures. 1-march-2010 Bug: Note the inputs to the package are in double. So make sure you are [Less]

mlpy - Machine Learning Python

Machine Learning PY is a high-performance Python/NumPy based package for Machine Learning.

ceslo

Assortment of Python and Perl scripts/modules for various tasks. Developed by Christine Slocum.

malas

Utilize all kind of Machine Learning approach to enhance antispam techniques.   Include antispam addins for mail client, and server-side antispam softwares.

oucware

Machine Learning based AntiSpam

mogandfriends

So far we have implemented:Mixture of Gaussians with full covariance Mixture of Gaussians with diagonal covariance matrix (diagonal matrix) Mixture of Gaussians with spherical covaraiance (identity matrix) Two versions of mixture of Gaussians with shrinkage Currently implementing:Mixture of ... [More] Probabalistic Principal Component Analyzers LDA QDA Two more versions of mixture of Gaussians with shrinkage [Less]

mlsharp

ML# (ML-Sharp) is a machine learning toolkit created in C# 3.0. It is similar to the Weka library for Java, and it is able to consume some Weka functionality via interop through IKVM. ML# has numerous advantages over Weka including a cleaner API and faster run-time execution.

rltb

Under construction.

termclassifier

A tool to find the relevance of candidate terms from a text corpus to any particular topic/sub-domain using a term classification driven approach. The system utilizes the lexical and contextual profiles of the candidate and domain-representing "Resource Terms" (Seed and Ontological). The ... [More] lexical and contextual profiles of candidate terms are compared with those of Resource Terms to measure their relevance to the topic of interest. [Less]