About: MLweb is an open source project that aims at bringing machine learning capabilities into web pages and web applications, while maintaining all computations on the client side. It includes (i) a javascript library to enable scientific computing within web pages, (ii) a javascript library implementing machine learning algorithms for classification, regression, clustering and dimensionality reduction, (iii) a web application providing a matlablike development environment. Changes:

About: Scriptfriendly commandline tools for machine learning and data mining tasks. (The commandline tools wrap functionality from a public domain C++ class library.) Changes:Added support for CUDA GPUparallelized neural network layers, and several other new features. Full list of changes at http://waffles.sourceforge.net/docs/changelog.html

About: Tapkee is an efficient and flexible C++ template library for dimensionality reduction. Changes:Initial Announcement on mloss.org.

About: This is an optimization library based on Social Impact Theory(SITO). The optimizer works in the same way as PSO and GA. Changes:A new variant 'Continuous Opinion Dynamics Optimizer (CODO)' has been implemented in this version. Minor changes in implementation of objective function.

About: A Matlab implementation of Multilinear PCA (MPCA) and MPCA+LDA for dimensionality reduction of tensor data with sample code on gait recognition Changes:

About: Divvy is a Mac OS X application for performing dimensionality reduction, clustering, and visualization. Changes:Initial Announcement on mloss.org.

About: A Matlab implementation of Uncorrelated Multilinear Discriminant Analysis (UMLDA) for dimensionality reduction of tensor data via tensortovector projection Changes:Initial Announcement on mloss.org.

About: A Matlab implementation of Uncorrelated Multilinear PCA (UMPCA) for dimensionality reduction of tensor data via tensortovector projection Changes:Initial Announcement on mloss.org.

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: 1839, January 2008. Changes:Initial Announcement on mloss.org.

About: This package is a set of Matlab scripts that implements the algorithms described in the submitted paper: "LpLq Sparse Linear and Sparse Multiple Kernel MultiTask Learning". Changes:Initial Announcement on mloss.org.

About: Correlative Matrix Mapping (CMM) provides a supervised linear data mapping into a Euclidean subspace of given dimension. Applications include denoising, visualization, labelspecific data preprocessing, and assessment of data attribute pairs relevant for the supervised mapping. Solving autoassociation problems yields linear multidimensional scaling, similar to PCA, but usually with more faithful lowdimensional mappings. Changes:Tue Jul 5 14:40:03 CEST 2011  Bugfixes and cleanups

About: Matlab code for semisupervised regression and dimensionality reduction using Hessian energy. Changes:Initial Announcement on mloss.org.

About: PLearn is a large C++ machinelearning 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.
