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Intended for .NET developers wanting to implement algorithms directly in a common .NET language (recommended: C#). Support for n-dim generic arrays, LAPACK, cells, logicals, 2D&3D plotting classes. [...]
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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 [...]
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LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, L1-loss linear SVM, and multi-class SVM
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The SHOGUN machine learning toolbox's focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It comes with a generic interface for SVMs, features several SVM and [...]
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A C++ toolkit containing machine learning algorithms and tools that facilitate creating complex software in C++ to solve real world problems.
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LaRank is an online solver for multiclass Support Vector Machines.
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SHARK is a modular C++ library for the design and optimization of adaptive systems. It provides methods for linear and nonlinear optimization, in particular evolutionary and gradient-based [...]
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Locally Weighted Projection Regression (LWPR) is a recent algorithm that achieves nonlinear function approximation in high dimensional spaces with redundant and irrelevant input dimensions. At its [...]
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The Sleipnir C++ library implements a variety of machine learning and data manipulation algorithms focusing on heterogeneous data integration and efficiency for large biological data collections.
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Nieme is a machine learning library for large-scale classification, regression and ranking. It relies on the framework of energy-based models which unifies several learning algorithms ranging from [...]
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A C++ library of machine learning algorithms and tools, and several demos that show how to use it.
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PyML is an interactive object oriented framework for machine learning in python with a focus on kernel methods.
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libDAI is a free/open source C++ library (licensed under GPL) that provides implementations of various (deterministic) approximate inference methods for discrete graphical models. libDAI supports [...]
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For modern biology, precise genome annotations are of prime importance as they allow the accurate definition of genic regions. We employ state of the art machine learning methods to assay and [...]
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OLL is a library supporting several for online-learning algorithms, which provides C++ library, and stand-alone programs for learning, predicting. OLL is specialized for large-scale, but sparse, [...]
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FlexCRFs is a conditional random field toolkit for segmenting and labeling sequence data written in C/C++ using STL library. It was implemented based on the theoretic model presented in (Lafferty et [...]
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GibbsLDA++: A C/C++ Implementation of Latent Dirichlet Allocation (LDA) using Gibbs Sampling for parameter estimation and inference. GibbsLDA++ is fast and is designed to analyze hidden/latent topic [...]
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The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL and utilizes Intel Integrated Performance [...]
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The UniverSVM is a SVM implementation written in C/C++. Its functionality comprises large scale transduction via CCCP optimization, sparse solutions via CCCP optimization and data-dependent [...]
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binsdfc is a command line implementation of the algorithm described in our 2007 NIPS paper. It computes spike density functions (SDF) or peri-stimulus time histograms (PSTH). Given that it performs [...]
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