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About: Support Vectors Machine library in .net with CUDA support. Library includes GPU SVM solver for kernels linear,RBF,Chi-Square and Exp Chi-Square which use NVIDIA CUDA technology. It allows for classification of feature rich sparse datasets through utilization of sparse matrix formats CSR, Ellpack-R or Sliced EllR-T Changes:Initial Announcement on mloss.org.
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About: Soltion developed by team Turtle Tamers in the ChaLearn Gesture Challenge (http://www.kaggle.com/c/GestureChallenge2) Changes:Initial Announcement on mloss.org.
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About: MLDemos is a user-friendly 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 non-numerical values) Added Dataset Editing panel to swap, delete and rename dimensions, classes or categorical values Several bug-fixes for display, import/export of data, classification performance New Algorithms and methodologies Added Projections to pre-process data (which can then be classified/regressed/clustered), with LDA, PCA, KernelPCA, ICA, CCA Added Grid-Search panel for batch-testing ranges of values for up to two parameters at a time Added One-vs-All multi-class classification for non-multi-class 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!)
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About: R version of GENetic Optimization Using Derivatives Changes:Fetched by r-cran-robot on 2013-04-01 00:00:08.101900
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About: Model-Based Boosting Changes:Fetched by r-cran-robot on 2013-04-01 00:00:06.324985
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About: L1 Regularization Path for Generalized Linear Models and Cox Proportional Hazards Model Changes:Fetched by r-cran-robot on 2013-04-01 00:00:05.305206
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About: Regularization paths for regression models with grouped covariates Changes:Fetched by r-cran-robot on 2013-04-01 00:00:05.489694
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About: Heteroscedastic Discriminant Analysis Changes:Fetched by r-cran-robot on 2013-04-01 00:00:05.551691
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About: The open-source C-package 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.
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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: 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 Laboratory for Recursive Partytioning Changes:Fetched by r-cran-robot on 2013-04-01 00:00:06.775432
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About: Mapping, pruning, and graphing tree models Changes:Fetched by r-cran-robot on 2013-04-01 00:00:06.263217
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About: Generalized Boosted Regression Models Changes:Fetched by r-cran-robot on 2013-04-01 00:00:05.019963
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About: SVDFeature is a toolkit for developing generic collaborative filtering algorithms by defining features. Changes:JMLR MLOSS version.
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About: a dbms for resonating neural networks. Create and use different types of machine learning algorithms. Changes:AIML compatible (AIML files can be imported); new 'Grid channel' for developing board games; improved topics editor; new demo project: ALice (from AIML); lots of bug-fixes and speed improvements
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About: Python Framework for Vector Space Modelling that can handle unlimited datasets (streamed input, online algorithms work incrementally in constant memory). Changes:
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About: L1 (lasso and fused lasso) and L2 (ridge) penalized estimation in GLMs and in the Cox model Changes:Fetched by r-cran-robot on 2013-04-01 00:00:06.939105
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About: L1 constrained estimation aka `lasso' Changes:Fetched by r-cran-robot on 2013-04-01 00:00:05.967868
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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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