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About: An implementation of the infinite hidden Markov model. Changes:Since 0.4: Removed dependency from lightspeed (now using statistics toolbox). Updated to newer matlab versions.
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About: Improved Predictors Changes:Fetched by r-cran-robot on 2013-04-01 00:00:05.613011
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About: PyBrain is a versatile machine learning library for Python. Its goal is to provide flexible, easy-to-use yet still powerful algorithms for machine learning tasks, including a variety of predefined [...] Changes:
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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.
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About: Orange is a component-based 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.
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About: Caffe aims to provide computer vision scientists with a clean, modifiable implementation of state-of-the-art deep learning algorithms. We believe that Caffe is the fastest available GPU CNN implementation. Caffe also provides seamless switching between CPU and GPU, which allows one to train models with fast GPUs and then deploy them on non-GPU clusters. Even in CPU mode, computing predictions on an image takes only 20 ms (in batch mode). Changes:LOTS of stuff: https://github.com/BVLC/caffe/releases/tag/v0.9999
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About: Nieme is a C++ machine learning library for large-scale classification, regression and ranking. It provides a simple interface available in C++, Python and Java and a user interface for visualization. Changes:Released Nieme 1.0
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About: This is the source code of the mloss.org website. Changes:Now works with newer django versions and fixes several warnings and minor bugs underneath. The only user visible change is probably that the subscription and bookmark buttons work again.
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About: JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random graphs/fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition. Changes:JProGraM 13.2 -- CHANGE LOG Release date: February 13, 2012 New features: -- Support for Fiedler random graphs/random field models for large-scale networks (ninofreno.graph.fiedler package); -- Various bugfixes and enhancements (especially in the ninofreno.graph and ninofreno.math package).
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About: A fast and scalable graph-based clustering algorithm based on the eigenvectors of the nonlinear 1-Laplacian. Changes:
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About: jblas is a fast linear algebra library for Java. jblas is based on BLAS and LAPACK, the de-facto industry standard for matrix computations, and uses state-of-the-art implementations like ATLAS for all its computational routines, making jBLAS very fast. Changes:Changes from 1.0:
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About: The CAM R-Java software provides a noval way to solve blind source separation problem. Changes:In this version, we fix the problem of not working under newest R version R-3.0.
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About: OpenNN is a software library written in C++ for advanced analytics. It implements neural networks, the most successful machine learning method. The library has been designed to learn from both data sets and mathematical models. Changes:New algorithms, correction of bugs.
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About: This toolbox provides functions for maximizing and minimizing submodular set functions, with applications to Bayesian experimental design, inference in Markov Random Fields, clustering and others. Changes:
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About: The EnsembleSVM library offers functionality to perform ensemble learning using Support Vector Machine (SVM) base models. In particular, we offer routines for binary ensemble models using SVM base classifiers. Experimental results have shown the predictive performance to be comparable with standard SVM models but with drastically reduced training time. Ensemble learning with SVM models is particularly useful for semi-supervised tasks. Changes:The library has been updated and features a variety of new functionality as well as more efficient implementations of original features. The following key improvements have been made:
The API and ABI have undergone significant changes, many of which are due to the transition to C++11.
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About: A MATLAB spectral clustering package to deal with large data sets. Our tool can handle large data sets (200,000 RCV1 data) on a 4GB memory general machine. Spectral clustering algorithm has been [...] Changes:
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About: The SUMO Toolbox is a Matlab toolbox that automatically builds accurate surrogate models (also known as metamodels or response surface models) of a given data source (e.g., simulation code, data set, script, ...) within the accuracy and time constraints set by the user. The toolbox minimizes the number of data points (which it selects automatically) since they are usually expensive. Changes:Incremental update, fixing some cosmetic issues, coincides with JMLR publication.
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About: Tapkee is an efficient and flexible C++ template library for dimensionality reduction. Changes:Initial Announcement on mloss.org.
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About: Generalized linear and additive models by likelihood based boosting Changes:Fetched by r-cran-robot on 2013-04-01 00:00:04.893311
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About: Bob is a free signal-processing 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/Changelog-from-1.1.4-to-1.2 https://github.com/idiap/bob/wiki/Changelog-from-1.2.0-to-1.2.1 https://github.com/idiap/bob/wiki/Changelog-from-1.2.1-to-1.2.2
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