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About: SenseClusters is a package of (mostly) Perl programs that allows a user to cluster similar contexts together using unsupervised knowledge-lean methods. These techniques have been applied to word [...] 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: 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 [...] Changes:Initial Announcement on mloss.org.
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About: 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 [...] Changes:Initial Announcement on mloss.org.
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About: 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 [...] Changes:Initial Announcement on mloss.org.
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About: It solves a classification problem over symmetric matrices with dual spectral norm (trace norm) regularization using a simple interior point method. It was successfully applied to single trial EEG [...] Changes:Initial Announcement on mloss.org.
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About: Recursive partitioning of longitudinal data using mixed-effects models Changes:Fetched by r-cran-robot on 2013-04-01 00:00:06.201307
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About: This is a C++ software designed to train large-scale SVMs for binary classification. The algorithm is also implemented in parallel (**PGPDT**) for distributed memory, strictly coupled multiprocessor [...] Changes:Initial Announcement on mloss.org.
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About: This package provides an implementation Schapire and Singer's AdaBoost.MH for multi-label classification. As a main feature, the package provides decision-tree weak learning, a generalization of [...] Changes:Initial Announcement on mloss.org.
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About: The GraphDemo provides Matlab GUIs to explore similarity graphs and their use in machine learning. It aims to highlight the behavior of different kinds of similarity graphs and to demonstrate their [...] Changes:Initial Announcement on mloss.org.
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About: SVMlin: Fast Linear SVMs for Supervised and Semi-supervised Learning Changes:Initial Announcement on mloss.org.
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About: *LHOTSE* is a C++ class library designed for the implementation of large, efficient scientific applications in Machine Learning and Statistics. Changes:Initial Announcement on mloss.org.
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About: The spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be [...] Changes:Initial Announcement on mloss.org.
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About: The SimpleSVM toolbox contains the svm solver of the same name. The current version includes C-SVM, HM-SVM and nu-SVM based on the regularization path. It will soon include OC-SVM, regularization [...] Changes:Initial Announcement on mloss.org.
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About: The incomplete Cholesky decomposition for a dense symmetric positive definite matrix A is a simple way of approximating A by a matrix of low rank (you can choose the rank). It has been used [...] Changes:Initial Announcement on mloss.org.
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About: You should never compute, maintain, or update the inverse of a symmetric positive definite matrix if you do not have to. Computing the inverse or manipulating it is inherently instable. You can [...] Changes:Initial Announcement on mloss.org.
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About: This page contains the implementation used in the paper „Experimental Design for Efficient Identification of Gene Regulatory Networks using Sparse Bayesian Models“ by Florian Steinke, Matthias [...] Changes:Initial Announcement on mloss.org.
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About: Efficient implementation of penalized multiple logistic regression (aka multi-class) with Mercer kernels, aka MAP approximation to the multi-class Gaussian process model. This includes [...] Changes:Initial Announcement on mloss.org.
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