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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: BSVM solves support vector machines (SVM) for the solution of large classification and regression problems. It includes three methods 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 TiMBL software package is a fast, decision-tree-based implementation of k-nearest neighbor classification. The package includes the IB1, IB2, TRIBL, TRIBL2, and IGTree algorithms, and offers [...] Changes:Initial Announcement on mloss.org.
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About: This is a large scale online learning implementation with several useful features. See the webpage for more details. Changes:Initial Announcement on mloss.org.
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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: Tekkotsu is a high-level framework for robot programming that provides primitives for perception, manipulation, navigation, and control. It supports a variety of robot platforms. 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: 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: 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: PLearn is a large C++ machine-learning library with a set of Python tools and Python bindings. It is mostly a research platform for developing novel algorithms, and is being used extensively at [...] Changes:Initial Announcement on mloss.org.
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About: ChemCpp is a C++ toolbox for chemoinformatics focusing on the computation of kernel functions between chemical compounds. 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: PALMA computes the optimal spliced alignment of a mRNA sequence to a genomic sequence. The main python script takes two FASTA files containing the target (e.g. a DNA sequence, part of the genome) [...] 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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