About: CARP: The Clustering Algorithms’ Referee Package Changes:Generalized overlap error and some bugs have been fixed

About: Q. Dong, Twodimensional relaxed representation, Neurocomputing, 121:248253, 2013, http://dx.doi.org/10.1016/j.neucom.2013.04.044 Changes:Initial Announcement on mloss.org.

About: Bob is a free signalprocessing and machine learning toolbox originally developed by the Biometrics group at Idiap Research Institute, in Switzerland. Changes:Bob 1.2.0 comes about 1 year after we released Bob 1.0.0. This new release comes with a big set of new features and lots of changes under the hood to make your experiments run even smoother. Some statistics: Diff URL: https://github.com/idiap/bob/compare/v1.1.4...HEAD Commits: 629 Files changed: 954 Contributors: 7 Here is a quick list of things you should pay attention for while integrating your satellite packages against Bob 1.2.x:
For a detailed list of changes and additions, please look at our Changelog page for this release and minor updates: https://github.com/idiap/bob/wiki/Changelogfrom1.1.4to1.2 https://github.com/idiap/bob/wiki/Changelogfrom1.2.0to1.2.1 https://github.com/idiap/bob/wiki/Changelogfrom1.2.1to1.2.2

About: DDN learns and visualize differential dependency networks from conditionspecific data. Changes:Initial Announcement on mloss.org.

About: An audio editing tool for singlechannel source separation. Changes:Stereo processing, bug fixes, UI updates.

About: Embarrassingly Parallel Array Computing: EPAC is a machine learning workflow builder. Changes:Initial Announcement on mloss.org.

About: MyMediaLite is a lightweight, multipurpose library of recommender system algorithms. Changes:Mostly bug fixes. For details see: https://github.com/zenogantner/MyMediaLite/blob/master/doc/Changes

About: A library for artificial neural networks. Changes:Added algorithms:

About: Ankus is an open source data mining / machine learning based MapReduce that supports a variety of advanced algorithms. Changes:Initial Announcement on mloss.org.

About: The Rchemcpp package implements the marginalized graph kernel and extensions, Tanimoto kernels, graph kernels, pharmacophore and 3D kernels suggested for measuring the similarity of molecules. Changes:Moved from CRAN to Bioconductor. Improved handling of molecules, visualization and examples.

About: A Matlab implementation of Multilinear PCA (MPCA) and MPCA+LDA for dimensionality reduction of tensor data with sample code on gait recognition Changes:

About: The mission of this project is to build and support a community interested in machine learning and machine intelligence based on modeling the neocortex and the principles upon which it works. 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: Bayesian statespace modelling and inference on highperformance computer hardware. Changes:Initial Announcement on mloss.org.

About: This toolbox implements a novel visualization technique called Sectors on Sectors (SonS), and a extended version called Multidimensional Sectors on Sectors (MDSonS), for improving the interpretation of several data mining algorithms. The MDSonS method makes use of Multidimensional Scaling (MDS) to solve the main drawback of the previous method, namely, the lack of representing distances between pairs of clusters. These methods have been applied for visualizing the results of hierarchical clustering, Growing Hierarchical SelfOrganizing Maps (GHSOM), classification trees and several manifolds. These methods make possible to extract all the existing relationships among centroids’ attributes at any hierarchy level. Changes:Initial Announcement on mloss.org.

About: A fast and robust learning of Bayesian networks Changes:Initial Announcement on mloss.org.

About: HLearn makes simple machine learning routines available in Haskell by expressing them according to their algebraic structure Changes:Updated to version 1.0

About: Support Vectors Machine library in .net with CUDA support. Library includes GPU SVM solver for kernels linear,RBF,ChiSquare and Exp ChiSquare which use NVIDIA CUDA technology. It allows for classification of feature rich sparse datasets through utilization of sparse matrix formats CSR, EllpackR or Sliced EllRT Changes:Initial Announcement on mloss.org.

About: MLDemos is a userfriendly visualization interface for various machine learning algorithms for classification, regression, clustering, projection, dynamical systems, reward maximisation and reinforcement learning. Changes:New Visualization and Dataset Features Added 3D visualization of samples and classification, regression and maximization results Added Visualization panel with individual plots, correlations, density, etc. Added Editing tools to drag/magnet data, change class, increase or decrease dimensions of the dataset Added categorical dimensions (indexed dimensions with nonnumerical values) Added Dataset Editing panel to swap, delete and rename dimensions, classes or categorical values Several bugfixes for display, import/export of data, classification performance New Algorithms and methodologies Added Projections to preprocess data (which can then be classified/regressed/clustered), with LDA, PCA, KernelPCA, ICA, CCA Added GridSearch panel for batchtesting ranges of values for up to two parameters at a time Added OnevsAll multiclass classification for nonmulticlass algorithms Trained models can now be kept and tested on new data (training on one dataset, testing on another) Added a dataset generator panel for standard toy datasets (e.g. swissroll, checkerboard,...) Added a number of clustering, regression and classification algorithms (FLAME, DBSCAN, LOWESS, CCA, KMEANS++, GP Classification, Random Forests) Added Save/Load Model option for GMMs and SVMs Added Growing Hierarchical Self Organizing Maps (original code by Michael Dittenbach) Added Automatic Relevance Determination for SVM with RBF kernel (Thanks to Ashwini Shukla!)

About: Orange is a componentbased machine learning and data mining software. It includes a friendly yet powerful and flexible graphical user interface for visual programming. For more advanced use(r)s, [...] Changes:The core of the system (except the GUI) no longer includes any GPL code and can be licensed under the terms of BSD upon request. The graphical part remains under GPL. Changed the BibTeX reference to the paper recently published in JMLR MLOSS.
