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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: 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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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: This is an implementation of variational Dirichlet process Gaussian mixtures. Thus, this works like the k-means, but it searched for the number of clusters as well. Couple algorithms are [...] Changes:Initial Announcement on mloss.org.
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About: The High-Dimensional Data Clustering (HDDC) toolbox contains an efficient unsupervised classifier for high-dimensional data. This classifier is based on a mixture of Gaussian models adapted for [...] Changes:Initial Announcement on mloss.org.
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About: Code for automatically selecting the kernel parameters of an SVM. It is based on a gradient descent minimization of either the radius/margin bound, the leave-one-out error, a validation error or the [...] Changes:Initial Announcement on mloss.org.
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About: The High Dimensional Discriminant Analysis (HDDA) toolbox contains an efficient supervised classifier for high-dimensional data. This classifier is based on Gaussian models adapted for [...] Changes:Initial Announcement on mloss.org.
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About: Itemset boosting (iBoost) performs linear regression in the complete space of power sets of mutations. It implements a forward feature selection procedure where, in each iteration, one mutation [...] 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: Very simple code for training SVMs in the primal. Works particularly well on sparse linear problems. In the non-linear case the entire kernel matrix needs to be computed, so for large problems it is [...] 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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About: This is a set of MATLAB(R) functions and MEX files which I wrote to make working with this system somewhat bearable. They allow to call BLAS and LAPACK functions, which do very efficient dense [...] Changes:Initial Announcement on mloss.org.
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About: The gboost toolbox is a framework for classification of connected, undirected, labeled graphs. Changes:Initial Announcement on mloss.org.
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