About: The goal of this project is to provide code for reading and writing machine learning data sets for as many programming languages as possible. Changes:Forgot to include the Java sources.

About: Gradient Boosted Regression Trees with ErrorsinVariables Changes:Fetched by rcranrobot on 20120601 00:00:05.010630

About: Pynopticon is a toolbox that allows you to create and train your own object recognition classifiers. It makes rapid prototyping of object recognition work flows a snap. Simply create a dataset of [...] Changes:Initial Announcement on mloss.org.

About: A library for fast computation of Gauss transforms in multiple dimensions, using the Improved Fast Gauss Transform and a tree data structure. This library is useful for efficient Kernel Density [...] Changes:Initial Announcement on mloss.org.

About: This package contains an implementation of the Infinite Kernel Learning (IKL) algorithm and the SimpleMKL algorithm. This is realized by building on CoinIpopt3.3.5 and Libsvm. Changes:Initial Announcement on mloss.org.

About: A Kmeans clustering implementation for commandline, Python, Matlab and C. This algorithm yields the very same solution as standard Kmeans, even after each iteration. However it uses some triangle [...] Changes:Initial Announcement on mloss.org.

About: Aleph is both a multiplatform machine learning framework aimed at simplicity and performance, and a library of selected stateoftheart algorithms. Changes:Initial Announcement on mloss.org.

About: JNCC2 is the opensource implementation of the Naive Credal Classifier2 (NCC2), i.e., an extension of Naive Bayes towards imprecise probabilities, designed to deliver robust classifications even on [...] Changes:Initial Announcement on mloss.org.

About: This software contains several matlab scripts for computing the RDE (relevant dimensionality estimate). The RDE measures the number of leading PCA components in feature space which contain the [...] Changes:Initial Announcement on mloss.org.

About: BenchMarking Via Weka is a clientserver architecture that supports interoperability between different machine learning systems. Machine learning systems need to provide mechanisms for processing [...] Changes:Initial Announcement on mloss.org.

About: Classification and Regression Training LSF Style: Augment some caret functions for parallel processing Changes:Initial Announcement on mloss.org.

About: Classification and Regression Training in Parallel Using NetworkSpaces: Augment some caret functions using parallel processing Changes:Initial Announcement on mloss.org.

About: CVX is a Matlabbased modeling system for convex optimization. CVX turns Matlab into a modeling language, allowing constraints and objectives to be specified using standard Matlab expression syntax. [...] Changes:Initial Announcement on mloss.org.

About: Eblearn is an objectoriented C++ library that implements various Changes:Initial Announcement on mloss.org.

About: Experiment Databases for Machine Learning is a large public database of machine learning experiments as well as a framework for producing similar databases for specific goals. It provides a way to [...] Changes:Initial Announcement on mloss.org.

About: The Chestnut Machine Learning Library is a suite of machine learning algorithms written in Python with some code written in C for efficiency. Most algorithms are called with a simple, functional API [...] Changes:Initial Announcement on mloss.org.

About: SnOB is a C++ library implementing fast Fourier transforms on the symmetric group (group of permutations). Such Fourier transforms are used by some ranking and identity management algorithms, as [...] Changes:Initial Announcement on mloss.org.

About: Java package implementing a kernel for (molecular) graphs based on iterative graph similarity and optimal assignments. Changes:Initial Announcement on mloss.org.

About: aiParts implements the HighHope technique  options have models of emotions which affect and are affected by repeated attempts to solve a multidecision problem. C++ classes for AI development. Changes:Initial Announcement on mloss.org.
