About: Scriptfriendly commandline tools for machine learning and data mining tasks. (The commandline tools wrap functionality from a public domain C++ class library.) Changes:Added support for CUDA GPUparallelized neural network layers, and several other new features. Full list of changes at http://waffles.sourceforge.net/docs/changelog.html

About: This package is an implementation of a linear RankSVM solver with nonconvex regularization. Changes:Initial Announcement on mloss.org.

About: PyStruct is a framework for learning structured prediction in Python. It has a modular interface, similar to the wellknown SVMstruct. Apart from learning algorithms it also contains model formulations for popular CRFs and interfaces to many inference algorithm implementation. Changes:Initial Announcement on mloss.org.

About: Efficient implementation of SemiStochastic Gradient Descent algorithm (S2GD) for training logistic regression (L2regularized). Changes:Initial Announcement on mloss.org.

About: This package implements Ideal PCA in MATLAB. Ideal PCA is a (cross)kernel based feature extraction algorithm which is (a) a faster alternative to kernel PCA and (b) a method to learn data manifold certifying features. Changes:Initial Announcement on mloss.org.

About: Document/Text preprocessing for topic models: suite of Perl scripts for preprocessing text collections to create dictionaries and bag/list files for use by topic modelling software. Changes:Moved distribution and code across to GitHub. Changed "ldac" format to have 0 offset for word indices. Added "document frequency" (df) filtering on selection of tokens for linkTables. Playing with linkParse but its still unuseable generally.

About: Scalable learning of global, multitask and local metrics from data Changes:Initial Announcement on mloss.org.

About: Learning string edit distance / similarity from data Changes:Initial Announcement on mloss.org.

About: Big Random Forests Changes:Fetched by rcranrobot on 20150101 00:00:04.544126

About: Gradient Boosting Changes:Fetched by rcranrobot on 20150101 00:00:04.939699

About: SAMOA is a platform for mining big data streams. It is a distributed streaming machine learning (ML) framework that contains a programing abstraction for distributed streaming ML algorithms. Changes:Initial Announcement on mloss.org.

About: DAL is an efficient and flexibible MATLAB toolbox for sparse/lowrank learning/reconstruction based on the dual augmented Lagrangian method. Changes:

About: Estimates statistical significance of association between variables and their principal components (PCs). Changes:Initial Announcement on mloss.org.

About: DRVQ is a C++ library implementation of dimensionalityrecursive vector quantization, a fast vector quantization method in highdimensional Euclidean spaces under arbitrary data distributions. It is an approximation of kmeans that is practically constant in data size and applies to arbitrarily high dimensions but can only scale to a few thousands of centroids. As a byproduct of training, a tree structure performs either exact or approximate quantization on trained centroids, the latter being not very precise but extremely fast. Changes:Initial Announcement on mloss.org.

About: hapFabia is an R package for identification of very short segments of identity by descent (IBD) characterized by rare variants in large sequencing data. It detects 100 times smaller segments than previous methods. Changes:o citation update o plot function improved

About: hapFabia is an R package for identification of very short segments of identity by descent (IBD) characterized by rare variants in large sequencing data. Changes:o citation update o plot function improved

About: A library for calculating and accessing generalized Stirling numbers of the second kind, which are used for inference in PoissonDirichlet processes. Changes:Initial Announcement on mloss.org.

About: Evolutionary Learning of Globally Optimal Trees Changes:Fetched by rcranrobot on 20140501 00:00:05.459097

About: The glmie toolbox contains scalable estimation routines for GLMs (generalised linear models) and SLMs (sparse linear models) as well as an implementation of a scalable convex variational Bayesian inference relaxation. We designed the glmie package to be simple, generic and easily expansible. Most of the code is written in Matlab including some MEX files. The code is fully compatible to both Matlab 7.x and GNU Octave 3.2.x. Probabilistic classification, sparse linear modelling and logistic regression are covered in a common algorithmical framework allowing for both MAP estimation and approximate Bayesian inference. Changes:added factorial mean field inference as a third algorithm complementing expectation propagation and variational Bayes generalised nonGaussian potentials so that affine instead of linear functions of the latent variables can be used

About: ALgebraic COmbinatorial COmpletion of MAtrices. A collection of algorithms to impute or denoise single entries in an incomplete rank one matrix, to determine for which entries this is possible with any algorithm, and to provide algorithmindependent error estimates. Includes demo scripts. Changes:Initial Announcement on mloss.org.
