About: Elefant is an open source software platform for the Machine Learning community licensed under the Mozilla Public License (MPL) and developed using Python, C, and C++. We aim to make it the platform [...] Changes:This release contains the Stream module as a first step in the direction of providing C++ library support. Stream aims to be a software framework for the implementation of large scale online learning algorithms. Large scale, in this context, should be understood as something that does not fit in the memory of a standard desktop computer. Added Bundle Methods for Regularized Risk Minimization (BMRM) allowing to choose from a list of loss functions and solvers (linear and quadratic). Added the following loss classes: BinaryClassificationLoss, HingeLoss, SquaredHingeLoss, ExponentialLoss, LogisticLoss, NoveltyLoss, LeastMeanSquareLoss, LeastAbsoluteDeviationLoss, QuantileRegressionLoss, EpsilonInsensitiveLoss, HuberRobustLoss, PoissonRegressionLoss, MultiClassLoss, WinnerTakesAllMultiClassLoss, ScaledSoftMarginMultiClassLoss, SoftmaxMultiClassLoss, MultivariateRegressionLoss Graphical User Interface provides now extensive documentation for each component explaining state variables and port descriptions. Changed saving and loading of experiments to XML (thereby avoiding storage of large input data structures). Unified automatic input checking via new static typing extending Python properties. Full support for recursive composition of larger components containing arbitrary statically typed state variables.

About: RLGlue allows agents, environments, and experiments written in Java, C/C++, Matlab, Python, and Lisp to inter operate, accelerating research by promoting software reuse in the community. Changes:RLGlue paper has been published in JMLR.

About: This package implements the “Online Random Forests” (ORF) algorithm of Saffari et al., ICCVOLCV 2009. This algorithm extends the offline Random Forests (RF) to learn from online training data samples. ORF is a multiclass classifier which is able to learn the classifier without 1vsall or 1vs1 binary decompositions. Changes:Initial Announcement on mloss.org.

About: EANT Without Structural Optimization is used to learn a policy in either complete or partially observable reinforcement learning domains of continuous state and action space. Changes:Initial Announcement on mloss.org.

About: Source code for EM approximate learning in the Latent Topic Hypertext Model. Changes:Initial Announcement on mloss.org.

About: BioSig is a software library for biomedical signal processings. Besides several other modules, one modul (t400) provides a common interface (train_sc.m and test_sc.m) to various classification [...] Changes:Update of project information: machine learning and classification tools are moved to the NaNtoolbox.

About: This software implements the Dirichlet Forest (DF) Prior within the Latent Dirichlet Allocation (LDA) model. When combined with LDA, the Dirichlet Forest Prior allows the user to encode domain knowledge (mustlinks and cannotlinks between words) into the prior on topicword multinomials. Changes:Initial Announcement on mloss.org.

About: This software implements the DeltaLDA model, which is a modification of the Latent Dirichlet Allocation (LDA) model. DeltaLDA can use multiple topic mixing weight priors to jointly model multiple [...] Changes:fixed some npy_intp[] memory leaks fixed phi normalization bug

About: The Computational Infrastructure for Operations Research (COINOR) project is an initiative to spur the development of opensource software for the operations research community. Changes:Initial Announcement on mloss.org.

About: SeDuMi is a software package to solve optimization problems over symmetric cones. This includes linear, quadratic, second order conic and semidefinite optimization, and any combination of these. Changes:Initial Announcement on mloss.org.

About: The Easysvm package provides a set of tools based on the Shogun toolbox allowing to train and test SVMs in a simple way. Changes:Fixes for shogun 0.7.3.

About: CMixSim is an open source package written in C for simulating finite mixture models with Gaussian components. With a vast number of clustering algorithms, evaluating performance is important. CMixSim provides an easy and convenient way of generating datasets from Gaussian mixture models with different levels of clustering complexity. CMixSim is released under the GNU GPL license. Changes:Initial Announcement on mloss.org.

About: ARTS is an accurate predictor for Transcription Start Sites (TSS). Changes:Initial Announcement on mloss.org.

About: OLL is a library supporting several for onlinelearning algorithms, which provides C++ library, and standalone programs for learning, predicting. OLL is specialized for largescale, but sparse, [...] Changes:Initial Announcement on mloss.org.

About: Ohmm is a library for learning hidden Markov models by using Online EM algorithm. This library is specialized for large scale data; e.g. 1 million words. The output includes parameters, and estimation results. Changes:Initial Announcement on mloss.org.

About: C++ Library for Highlevel Computer Vision Tasks Changes:Initial Announcement on mloss.org.

About: This package contains functions to estimate linear and nonlinear regression methods with Penalized Partial Least Squares. Changes:

About: This software is aimed at performing supervised/unsupervised learning on graph data, where each graph is represented as binary indicators of subgraph features. Changes:Initial Announcement on mloss.org.

About: stroll (STRuctured Output Learning Library) is a library for Structured Output Learning. Changes:Initial Announcement on mloss.org.

About: CoFiRank is a Collaborative Filtering system based on matrix factorization. CoFiRank is based on the idea that it is better to predict the relative order of preferences (ranking) instead of the absolute rating. Changes:Initial Announcement on mloss.org.
