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Logo r-cran-partykit 0.1-5

by r-cran-robot - March 22, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 2081 views, 462 downloads, 0 subscriptions

About: A Toolkit for Recursive Partytioning

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Fetched by r-cran-robot on 2013-04-01 00:00:06.838561


Logo r-cran-penalizedSVM 1.1

by r-cran-robot - August 2, 2010, 00:00:00 CET [ Project Homepage BibTeX Download ] 2247 views, 456 downloads, 0 subscriptions

About: Feature Selection SVM using penalty functions

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Fetched by r-cran-robot on 2013-04-01 00:00:07.509844


Logo GP RTSS 1.0

by marc - March 21, 2012, 08:43:52 CET [ BibTeX BibTeX for corresponding Paper Download ] 1411 views, 455 downloads, 1 subscription

About: Gaussian process RTS smoothing (forward-backward smoothing) based on moment matching.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-ncvreg 2.5-0

by r-cran-robot - March 15, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 2149 views, 453 downloads, 0 subscriptions

About: Regularization paths for SCAD- and MCP-penalized regression models

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Fetched by r-cran-robot on 2013-04-01 00:00:06.449164


Logo treelearn 1

by iskander - September 21, 2011, 16:12:27 CET [ Project Homepage BibTeX Download ] 1981 views, 451 downloads, 1 subscription

About: A python implementation of Breiman's Random Forests.

Changes:

Initial Announcement on mloss.org.


Logo OpenGM 2 2.0.2 beta

by opengm - June 1, 2012, 14:33:53 CET [ Project Homepage BibTeX Download ] 2043 views, 448 downloads, 1 subscription

About: A C++ Library for Discrete Graphical Models

Changes:

Initial Announcement on mloss.org.


Logo Graphical Models and Conditional Random Fields Toolbox 2

by jdomke - January 5, 2012, 15:38:20 CET [ Project Homepage BibTeX Download ] 1940 views, 447 downloads, 1 subscription

About: This is a Matlab/C++ "toolbox" of code for learning and inference with graphical models. It is focused on parameter learning using marginalization in the high-treewidth setting.

Changes:

Initial Announcement on mloss.org.


About: In this paper, we propose an improved principal component analysis based on maximum entropy (MaxEnt) preservation, called MaxEnt-PCA, which is derived from a Parzen window estimation of Renyi’s quadratic entropy. Instead of minimizing the reconstruction error either based on L2-norm or L1-norm, the MaxEnt-PCA attempts to preserve as much as possible the uncertainty information of the data measured by entropy. The optimal solution of MaxEnt-PCA consists of the eigenvectors of a Laplacian probability matrix corresponding to the MaxEnt distribution. MaxEnt-PCA (1) is rotation invariant, (2) is free from any distribution assumption, and (3) is robust to outliers. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed linear method as compared to other related robust PCA methods.

Changes:

Initial Announcement on mloss.org.


Logo Large margin filtering 0.9

by rflamary - February 18, 2012, 15:50:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2088 views, 440 downloads, 1 subscription

About: Matlab SVM toolbox for learning large margin filters in signal or images.

Changes:

Initial Announcement on mloss.org.


Logo HLearn 1.0

by mikeizbicki - May 9, 2013, 05:58:18 CET [ Project Homepage BibTeX Download ] 1976 views, 434 downloads, 1 subscription

About: HLearn makes simple machine learning routines available in Haskell by expressing them according to their algebraic structure

Changes:

Updated to version 1.0


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