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About: This Java software implements Profile Hidden Markov Models (PHMMs) for protein classification for the WEKA workbench. Standard PHMMs and newly introduced binary PHMMs are used. In addition the software allows propositionalisation of PHMMs. Changes:description changed

About: A Sortware for All Pairs Similarity Search Changes:Initial Announcement on mloss.org.

About: KeplerWeka represents the integration of all the functionality of the WEKA Machine Learning Workbench into the opensource scientific workflow Kepler. Among them are classification, [...] Changes:

About: Ordinal classification tree functions Changes:Initial Announcement on mloss.org by rcranrobot

About: OpenViBE is an opensource platform that enables to design, test and use BrainComputer Interfaces (BCI). Broadly speaking, OpenViBE can be used in many realtime Neuroscience applications [...] Changes:New release 0.8.0.

About: The SUMO Toolbox is a Matlab toolbox that automatically builds accurate surrogate models (also known as metamodels or response surface models) of a given data source (e.g., simulation code, data set, script, ...) within the accuracy and time constraints set by the user. The toolbox minimizes the number of data points (which it selects automatically) since they are usually expensive. Changes:Incremental update, fixing some cosmetic issues, coincides with JMLR publication.

About: Moses is a statistical machine translation system that allows you to automatically train translation models for any language pair. All you need is a collection of translated texts (parallel corpus). An efficient search algorithm finds quickly the highest probability translation among the exponential number of choices. Changes:Initial Announcement on mloss.org.

About: jblas is a fast linear algebra library for Java. jblas is based on BLAS and LAPACK, the defacto industry standard for matrix computations, and uses stateoftheart implementations like ATLAS for all its computational routines, making jBLAS very fast. Changes:Changes from 1.0:

About: redsvd is a library for solving several matrix decomposition (SVD, PCA, eigen value decomposition) redsvd can handle very large matrix efficiently, and optimized for a truncated SVD of sparse matrices. For example, redsvd can compute a truncated SVD with top 20 singular values for a 100K x 100K matrix with 10M nonzero entries in about two second. Changes:Initial Announcement on mloss.org.

About: The gmm toolbox contains code for density estimation using mixtures of Gaussians: Starting from simple kernel density estimation with spherical and diagonal Gaussian kernels over manifold Parzen window until mixtures of penalised full Gaussians with only a few components. The toolbox covers many Gaussian mixture model parametrisations from the recent literature. Most prominently, the package contains code to use the Gaussian Process Latent Variable Model for density estimation. Most of the code is written in Matlab 7.x including some MEX files. Changes:Initial Announcement on mloss.org
