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About: The open source ErrorCorrecting Output Codes (ECOC) library contains both stateoftheart coding and decoding designs, as well as the option to include your own coding, decoding, and base classifier. Changes:Initial Announcement on mloss.org.

About: This evaluation toolkit provides a unified framework for evaluating bagofwords based encoding methods over several standard image classification datasets. Changes:Initial Announcement on mloss.org.

About: This page contains the implementation used in the paper „Experimental Design for Efficient Identification of Gene Regulatory Networks using Sparse Bayesian Models“ by Florian Steinke, Matthias [...] 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: Scalable tensor factorization Changes:

About: FABIA is a biclustering algorithm that clusters rows and columns of a matrix simultaneously. Consequently, members of a row cluster are similar to each other on a subset of columns and, analogously, members of a column cluster are similar to each other on a subset of rows. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. Applications include detection of transcriptional modules in gene expression data and identification of haplotypes/>identity by descent< consisting of rare variants obtained by next generation sequencing. Changes:CHANGES IN VERSION 2.8.0NEW FEATURES
CHANGES IN VERSION 2.4.0
CHANGES IN VERSION 2.3.1NEW FEATURES
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About: [FACTORIE](http://factorie.cs.umass.edu) is a toolkit for deployable probabilistic modeling, implemented as a software library in [Scala](http://scalalang.org). It provides its users with a succinct language for creating [factor graphs](http://en.wikipedia.org/wiki/Factor_graph), estimating parameters and performing inference. It also has implementations of many machine learning tools and a full NLP pipeline. Changes:Initial Announcement on mloss.org.

About: FAST is an implementation of Hidden Markov Models with Features. It allows features to modify both emissions and transition probabilities. Changes:Initial Announcement on mloss.org.

About: The package "fastclime" provides a method of recover the precision matrix efficiently by applying parametric simplex method. The computation is based on a linear optimization solver. It also contains a generic LP solver and a parameterized LP solver using parametric simplex method. Changes:Initial Announcement on mloss.org.

About: The opensource Cpackage fastICA implements the fastICA algorithm of Aapo Hyvarinen et al. (URL: http://www.cs.helsinki.fi/u/ahyvarin/) to perform Independent Component Analysis (ICA) and Projection Pursuit. fastICA is released under the GNU Public License (GPL). Changes:Initial Announcement on mloss.org.
