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Logo r-cran-BayesTree 0.3-1.2

by r-cran-robot - November 2, 2014, 00:00:00 CET [ Project Homepage BibTeX Download ] 5114 views, 1098 downloads, 1 subscription

About: Bayesian Additive Regression Trees

Changes:

Fetched by r-cran-robot on 2015-01-01 00:00:04.425239


Logo libcluster 2.1

by dsteinberg - October 31, 2014, 23:27:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 623 views, 125 downloads, 2 subscriptions

About: An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more.

Changes:

Initial Announcement on mloss.org.


Logo LogRegCrowds, Logistic Regression from Crowds 1.0

by fmpr - October 30, 2014, 19:10:23 CET [ Project Homepage BibTeX Download ] 495 views, 126 downloads, 2 subscriptions

About: LogReg-Crowds is a collection of Julia implementations of various approaches for learning a logistic regression model multiple annotators and crowds, namely the works of Raykar et al. (2010), Rodrigues et al. (2013) and Dawid and Skene (1979).

Changes:

Initial Announcement on mloss.org.


About: This library implements the Optimum-Path Forest classifier for unsupervised and supervised learning.

Changes:

Initial Announcement on mloss.org.


Logo pySPACE 1.2

by krell84 - October 29, 2014, 15:36:28 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2531 views, 534 downloads, 1 subscription

About: pySPACE is the abbreviation for "Signal Processing and Classification Environment in Python using YAML and supporting parallelization". It is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface.

Changes:

improved testing, improved documentation, windows compatibility, more algorithms


Logo BACOM2 1.0

by fydennis - October 24, 2014, 15:25:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 611 views, 118 downloads, 2 subscriptions

About: revised version of BACOM

Changes:

Initial Announcement on mloss.org.


Logo CFSPCommunityDetection 1.0

by tbuehler - October 13, 2014, 05:36:24 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 691 views, 159 downloads, 1 subscription

About: A community detection method based on constrained fractional set programming (CFSP).

Changes:

Initial Announcement on mloss.org.


Logo BayesOpt, a Bayesian Optimization toolbox 0.7.2

by rmcantin - October 10, 2014, 19:12:59 CET [ Project Homepage BibTeX Download ] 10586 views, 2174 downloads, 4 subscriptions

About: BayesOpt is an efficient, C++ implementation of the Bayesian optimization methodology for nonlinear-optimization, experimental design and stochastic bandits. In the literature it is also called Sequential Kriging Optimization (SKO) or Efficient Global Optimization (EGO). There are also interfaces for C, Matlab/Octave and Python.

Changes:

-Fixed bugs and doc typos


Logo AugmentedSVM 1.0.0

by ashukla - October 2, 2014, 11:24:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 905 views, 183 downloads, 2 subscriptions

About: A MATLAB toolkit for performing generalized regression with equality/inequality constraints on the function value/gradient.

Changes:

Initial Announcement on mloss.org.


Logo hca 0.61

by wbuntine - September 10, 2014, 03:33:54 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6388 views, 1209 downloads, 4 subscriptions

About: Multi-core non-parametric and bursty topic models (HDP-LDA, DCMLDA, and other variants of LDA) implemented in C using efficient Gibbs sampling, with hyperparameter sampling and other flexible controls.

Changes:

Corrections to diagnostics and topic report. Correction to estimating alpha. Now estimating beta sometimes (when estimating phi).


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