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Logo Figue 1.0.1

by lerhumcbon - August 17, 2010, 04:03:35 CET [ Project Homepage BibTeX Download ] 3342 views, 799 downloads, 1 subscription

About: A collection of clustering algorithms implemented in Javascript.

Changes:

Initial Announcement on mloss.org.


Logo Some essential Matlab extensions 1.0

by mseeger - November 10, 2007, 22:15:31 CET [ Project Homepage BibTeX Download ] 3339 views, 911 downloads, 0 comments, 0 subscriptions

About: This is a set of MATLAB(R) functions and MEX files which I wrote to make working with this system somewhat bearable. They allow to call BLAS and LAPACK functions, which do very efficient dense [...]

Changes:

Initial Announcement on mloss.org.


Logo r-cran-relaxo 0.1-2

by r-cran-robot - June 1, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 3335 views, 848 downloads, 1 subscription

About: Relaxed Lasso

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:07.978325


About: Multi-class vector classification based on cost function-driven learning vector quantization , minimizing misclassification.

Changes:

Initial Announcement on mloss.org.


Logo LHOTSE 0.14

by mseeger - November 26, 2007, 21:12:19 CET [ Project Homepage BibTeX ] 3318 views, 27 downloads, 0 comments, 0 subscriptions

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.


Logo XGBoost v0.3.0

by crowwork - September 2, 2014, 02:43:31 CET [ Project Homepage BibTeX Download ] 3298 views, 630 downloads, 2 subscriptions

About: xgboost: eXtreme Gradient Boosting It is an efficient and scalable implementation of gradient boosting framework. The package includes efficient linear model solver and tree learning algorithm. The package can automatically do parallel computation with OpenMP, and it can be more than 10 times faster than existing gradient boosting packages such as gbm or sklearn.GBM . It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that user are also allowed to define there own objectives easily.

Changes:

New features: - R support that is now on CRAN

  • Faster tree construction module

  • Support for boosting from initial predictions

  • Linear booster is now parallelized, using parallel coordinated descent.


Logo Nen Beta

by pascal - February 19, 2012, 00:31:34 CET [ Project Homepage BibTeX Download ] 3276 views, 991 downloads, 1 subscription

About: 3-layer neural network for regression with sigmoid activation function and command line interface similar to LibSVM.

Changes:

Initial Announcement on mloss.org.


About: Nimfa is an open-source Python library that provides a unified interface to nonnegative matrix factorization algorithms. It includes implementations of state-of-the-art factorization methods, initialization approaches, and quality scoring. Both dense and sparse matrix representation are supported.

Changes:

Initial Announcement on mloss.org.


About: Stochastic neighbor embedding originally aims at the reconstruction of given distance relations in a low-dimensional Euclidean space. This can be regarded as general approach to multi-dimensional scaling, but the reconstruction is based on the definition of input (and output) neighborhood probability alone. The present implementation also allows for handling dissimilarity or score-induced neighborhood topologies and makes use of quasi 2nd order gradient-based (l-)BFGS optimization.

Changes:
  • gradient in xsne_fun.m fixed! (constant factor m was missing)

  • symmetry option re-introduced allowing for enabling symmetric and asymmetric versions of SNE and t-SNE


Logo Encog Machine Learning Framework 3.2

by jeffheaton - July 5, 2014, 23:47:06 CET [ Project Homepage BibTeX Download ] 3186 views, 731 downloads, 1 subscription

About: Encog is a Machine Learning framework for Java, C#, Javascript and C/C++ that supports SVM's, Genetic Programming, Bayesian Networks, Hidden Markov Models and other algorithms.

Changes:

Changes for Encog 3.2:

Issue #53: Fix Out Of Range Bug In BasicMLSequenceSet. Issue #52: Unhandled exception in Encog.Util.File.ResourceLoader.CreateStream (ResourceLoader.cs) Issue #50: Concurrency bugs in PruneIncremental Issue #48: Unit Tests Failing - TestHessian Issue #46: Couple of small fixes - Temporal DataSet and SCG training Issue #45: Fixed EndMinutesStrategy to correctly evaluate ShouldStop after the specified number of minutes have elapsed. Issue #44: Encog.ML.Data.Basic.BasicMLDataPairCentroid.Add() & .Remove() Issue #43: Unit Tests Failing - Matrix not full rank Issue #42: Nuget - NuSpec Issue #36: Load Examples easier


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