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About: This is an optimization library based on Social Impact Theory(SITO). The optimizer works in the same way as PSO and GA. Changes:minor changes
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About: A broad collection of script-friendly command-line tools for machine learning and data mining tasks. (The command-line tools wrap functionality from a C++ class library.) Changes:See the change log at http://waffles.sourceforge.net/changelog.html
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About: Tapkee is an efficient and flexible C++ template library for dimensionality reduction. Changes:Initial Announcement on mloss.org.
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About: Divvy is a Mac OS X application for performing dimensionality reduction, clustering, and visualization. Changes:Initial Announcement on mloss.org.
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About: A Matlab implementation of Uncorrelated Multilinear Discriminant Analysis (UMLDA) for dimensionality reduction of tensor data via tensor-to-vector projection Changes:Initial Announcement on mloss.org.
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About: A Matlab implementation of Uncorrelated Multilinear PCA (UMPCA) for dimensionality reduction of tensor data via tensor-to-vector projection Changes:Initial Announcement on mloss.org.
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About: This archive contains a Matlab implementation of the Multilinear Principal Component Analysis (MPCA) algorithm and MPCA+LDA, as described in the paper Haiping Lu, K.N. Plataniotis, and A.N. Venetsanopoulos, "MPCA: Multilinear Principal Component Analysis of Tensor Objects", IEEE Transactions on Neural Networks, Vol. 19, No. 1, Page: 18-39, January 2008. Changes:Initial Announcement on mloss.org.
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About: A Matlab implementation of Multilinear PCA (MPCA) and MPCA+LDA for dimensionality reduction of tensor data 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: 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: Matlab code for semi-supervised regression and dimensionality reduction using Hessian energy. 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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