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About: This project is a C++ toolkit containing machine learning algorithms and tools that facilitate creating complex software in C++ to solve real world problems. Changes:In addition to some bug fixes, this release also brings the following notable improvements to the library:
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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:Improved documentation and data handling.
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About: machine learning library in java for easy development of new kernels Changes:Version 2.0.
Warning: all classes have migrated under the fr.lip6.jkernelmachines package, which breaks backward compatibility, but was necessary to keep the project going on sanely.
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About: Accord.NET provides statistical analysis, machine learning, image processing and computer vision methods for .NET applications. The Accord.NET Framework extends the popular AForge.NET with new features, adding to a more complete environment for scientific computing in .NET. Changes:This release brings Cox's proportional hazards models and the partial Newton-Raphson learning algorithm. It also provides a reorganization of the (Hidden Conditional Random) Fields namespace, together with more bugfixes, improvements and optimizations. For a complete list of changes, please see the full release notes at the release details page.
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About: Matlab code for learning probabilistic SVM in the presence of uncertain labels. Changes:Added missing dataset function (thanks to Hao Wu)
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About: This package is a set of Matlab scripts that implements the algorithms described in the submitted paper: "Lp-Lq Sparse Linear and Sparse Multiple Kernel MultiTask Learning". Changes:Initial Announcement on mloss.org.
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About: The Kernel-Machine Library is a free (released under the LGPL) C++ library to promote the use of and progress of kernel machines. Changes:Updated mloss entry (minor fixes).
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About: OpenKernel is a library for creating, combining, learning and using kernels for machine learning applications. Changes:Initial Announcement on mloss.org.
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About: RLS2 is an instance of multiple kernel learning algorithm to simultaneously learn a regularized predictor and the kernel function. RLS2LIN is a version of RLS2 specialized to linear kernels on each feature. The package contains a set of scripts that implements RLS2 and RLS2LIN, together with a Graphic User Interface to load data, perform training, validation, and plot results. Changes:
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About: GPUML is a library that provides a C/C++ and MATLAB interface for speeding up the computation of the weighted kernel summation and kernel matrix construction on GPU. These computations occur commonly in several machine learning algorithms like kernel density estimation, kernel regression, kernel PCA, etc. Changes:Initial Announcement on mloss.org.
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About: kernlab provides kernel-based Machine Learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods kernlab [...] Changes:minor fixes in kcca and ksvm functions
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About: SHARK is a modular C++ library for the design and optimization of adaptive systems. It provides various machine learning and computational intelligence techniques. Changes:
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About: This package contains an implementation of the Infinite Kernel Learning (IKL) algorithm and the SimpleMKL algorithm. This is realized by building on Coin-Ipopt-3.3.5 and Libsvm. Changes:Initial Announcement on mloss.org.
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About: This software contains several matlab scripts for computing the RDE (relevant dimensionality estimate). The RDE measures the number of leading PCA components in feature space which contain the [...] Changes:Initial Announcement on mloss.org.
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About: Java package implementing a kernel for (molecular) graphs based on iterative graph similarity and optimal assignments. Changes:Initial Announcement on mloss.org.
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About: LaRank is an online solver for multiclass Support Vector Machines. Changes:Initial Announcement on mloss.org.
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About: Matlab Multiple Kernel Learning toolbox. Features : MKL for SVM Classification, Regression and MultiClass. It needs SVM-KM Toolbox Changes:Initial Announcement on mloss.org.
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About: SVM Toolbox fully written in Matlab (even the QP solver). Features : SVM, MultiClassSVM, One-Class, SV Regression, AUC-SVM and Rankboost, 1-norm SVM, Regularization Networks, Kernel Basis Pursuit [...] Changes:Initial Announcement on mloss.org.
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About: PyML is an interactive object oriented framework for machine learning in python with a focus on kernel methods. Changes:Initial Announcement on mloss.org.
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About: We provide some preliminary code for multiclass multiple kernel learning in Matlab using CPLEX as a base solver. Changes:Initial Announcement on mloss.org.
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