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About: PLEASD: A Matlab Toolbox for Structured Learning Changes:Initial Announcement on mloss.org.
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About: A general purpose library to process and predict sequences of elements using echo state networks. Changes:Initial Announcement on mloss.org.
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About: MLwizard recommends and optimizes classification algorithms based on meta-learning and is a software wizard fully integrated into RapidMiner but can be used as library as well. Changes:Faster parameter optimization using genetic algorithm with predefined start population.
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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 contains a python and a matlab implementation of the most widely used algorithms for multi-armed bandit problems. The purpose of this package is to provide simple environments for comparison and numerical evaluation of policies. Changes:Initial Announcement on mloss.org.
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About: The package provides a Lagrangian approach to the posterior regularization of given linear mappings. This is important in two cases, (a) when systems are under-determined and (b) when the external model for calculating the mapping is invariant to properties such as scaling. The software may be applied in cases when the external model does not provide its own regularization strategy. In addition, the package allows to rank attributes according to their distortion potential to a given linear mapping. Changes:Version 1.1 (May 23, 2012) memory and time optimizations distderivrel.m now supports assessing the relevance of attribute pairs Version 1.0 (Nov 9, 2011) * Initial Announcement on mloss.org.
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About: Fast C++ implementation of the variation of information (Meila 2003) and Rand index (Rand 1971) with MATLAB mex files Changes:Initial Announcement on mloss.org.
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About: Motivated by a need to classify high-dimensional, heterogeneous data from the bioinformatics domain, we developed ML-Flex, a machine-learning toolbox that enables users to perform two-class and multi-class classification analyses in a systematic yet flexible manner. ML-Flex was written in Java but is capable of interfacing with third-party packages written in other programming languages. It can handle multiple input-data formats and supports a variety of customizations. MLFlex provides implementations of various validation strategies, which can be executed in parallel across multiple computing cores, processors, and nodes. Additionally, ML-Flex supports aggregating evidence across multiple algorithms and data sets via ensemble learning. (See http://jmlr.csail.mit.edu/papers/volume13/piccolo12a/piccolo12a.pdf.) Changes:Initial Announcement on mloss.org.
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About: This local and parallel computation toolbox is the Octave and Matlab implementation of several localized Gaussian process regression methods: the domain decomposition method (Park et al., 2011, DDM), partial independent conditional (Snelson and Ghahramani, 2007, PIC), localized probabilistic regression (Urtasun and Darrell, 2008, LPR), and bagging for Gaussian process regression (Chen and Ren, 2009, BGP). Most of the localized regression methods can be applied for general machine learning problems although DDM is only applicable for spatial datasets. In addition, the GPLP provides two parallel computation versions of the domain decomposition method. The easiness of being parallelized is one of the advantages of the localized regression, and the two parallel implementations will provide a good guidance about how to materialize this advantage as software. Changes:Initial Announcement on mloss.org.
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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: 3-layer neural network for regression with sigmoid activation function and command line interface similar to LibSVM. Changes:Initial Announcement on mloss.org.
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About: Matlab SVM toolbox for learning large margin filters in signal or images. Changes:Initial Announcement on mloss.org.
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About: The SSA Toolbox is an efficient, platform-independent, standalone implementation of the Stationary Subspace Analysis algorithm with a friendly graphical user interface and a bridge to Matlab. Stationary Subspace Analysis (SSA) is a general purpose algorithm for the explorative analysis of non-stationary data, i.e. data whose statistical properties change over time. SSA helps to detect, investigate and visualize temporal changes in complex high-dimensional data sets. Changes:
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About: Learns gradient boosted regression tree ensembles in parallel on shared memory or cluster systems Changes:Initial Announcement on mloss.org.
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About: MLPlot is a lightweight plotting library written in Java. Changes:Initial Announcement on mloss.org.
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About: Multi-class vector classification based on cost function-driven learning vector quantization , minimizing misclassification. Changes:Initial Announcement on mloss.org.
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About: Fast Runtime-Flexible Multi-dimensional Arrays and Views for C++ Changes:Initial Announcement on mloss.org.
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About: Correlative Matrix Mapping (CMM) provides a supervised linear data mapping into a Euclidean subspace of given dimension. Applications include denoising, visualization, label-specific data preprocessing, and assessment of data attribute pairs relevant for the supervised mapping. Solving auto-association problems yields linear multidimensional scaling, similar to PCA, but usually with more faithful low-dimensional mappings. Changes:Tue Jul 5 14:40:03 CEST 2011 - Bugfixes and cleanups
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About: Grid-Soccer Simulator is a multi-agent soccer simulator in a grid-world environment. The environment provides a test-bed for machine-learning, and control algorithms, especially multi-agent reinforcement learning. Changes:Initial Announcement on mloss.org.
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About: The source code of the mldata.org site - a community portal for machine learning data sets. Changes:Initial Announcement on mloss.org.
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