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Showing Items 151-160 of 653 on page 16 of 66: First Previous 11 12 13 14 15 16 17 18 19 20 21 Next Last

Logo LASVM 1.1

by leonbottou - August 3, 2009, 15:50:30 CET [ Project Homepage BibTeX Download ] 12867 views, 2427 downloads, 0 subscriptions

About: Reference implementation of the LASVM online and active SVM algorithms as described in the JMLR paper. The interesting bit is a small C library that implements the LASVM process and reprocess [...]

Changes:

Minor bug fix


Logo 1SpectralClustering 1.1

by tbuehler - June 27, 2011, 10:45:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12837 views, 2518 downloads, 1 subscription

About: A fast and scalable graph-based clustering algorithm based on the eigenvectors of the nonlinear 1-Laplacian.

Changes:
  • fixed bug occuring when input graph is disconnected
  • reduced memory usage when input graph has large number of disconnected components
  • more user-friendly usage of main method OneSpectralClustering
  • faster computation of eigenvector initialization + now thresholded according to multicut-criterion
  • several internal optimizations

Logo Penalized Partial Least Squares Regression 1.03

by nkraemer - May 5, 2009, 19:53:20 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12790 views, 1972 downloads, 0 subscriptions

About: This package contains functions to estimate linear and nonlinear regression methods with Penalized Partial Least Squares.

Changes:
  • fixed several bugs
  • drastic speed-up of computation time

Logo SVM and Kernel Methods Toolbox 0.5

by arakotom - June 10, 2008, 21:29:39 CET [ Project Homepage BibTeX Download ] 12686 views, 3017 downloads, 2 subscriptions

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About: SVM Toolbox fully written in Matlab (even the QP solver). Features : SVM, MultiClassSVM, One-Class, SV Regression, AUC-SVM and Rankboost, 1-norm SVM, Regularization Networks, Kernel Basis Pursuit [...]

Changes:

Initial Announcement on mloss.org.


Logo Online Random Forests 0.11

by amirsaffari - October 3, 2009, 17:25:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12529 views, 2259 downloads, 1 subscription

About: This package implements the “Online Random Forests” (ORF) algorithm of Saffari et al., ICCV-OLCV 2009. This algorithm extends the offline Random Forests (RF) to learn from online training data samples. ORF is a multi-class classifier which is able to learn the classifier without 1-vs-all or 1-vs-1 binary decompositions.

Changes:

Initial Announcement on mloss.org.


Logo r-cran-LogicReg 1.5.3

by r-cran-robot - July 23, 2012, 00:00:00 CET [ Project Homepage BibTeX Download ] 12483 views, 2374 downloads, 0 subscriptions

About: Logic Regression

Changes:

Fetched by r-cran-robot on 2013-04-01 00:00:06.139495


Logo r-cran-ElemStatLearn 2015.6.26

by r-cran-robot - June 26, 2015, 00:00:00 CET [ Project Homepage BibTeX Download ] 12467 views, 2596 downloads, 3 subscriptions

About: Data Sets, Functions and Examples from the Book

Changes:

Fetched by r-cran-robot on 2017-10-01 00:00:09.022537


Logo r-cran-ahaz 1.14

by r-cran-robot - June 3, 2013, 00:00:00 CET [ Project Homepage BibTeX Download ] 12456 views, 2616 downloads, 0 subscriptions

About: Regularization for semiparametric additive hazards regression

Changes:

Fetched by r-cran-robot on 2017-10-01 00:00:04.114266


About: Infrastructure for representing, manipulating and analyzing transaction data and frequent patterns.

Changes:

Initial Announcement on mloss.org.


About: This local and parallel computation toolbox is the Octave and Matlab implementation of several localized Gaussian process regression methods: the domain decomposition method (Park et al., 2011, DDM), partial independent conditional (Snelson and Ghahramani, 2007, PIC), localized probabilistic regression (Urtasun and Darrell, 2008, LPR), and bagging for Gaussian process regression (Chen and Ren, 2009, BGP). Most of the localized regression methods can be applied for general machine learning problems although DDM is only applicable for spatial datasets. In addition, the GPLP provides two parallel computation versions of the domain decomposition method. The easiness of being parallelized is one of the advantages of the localized regression, and the two parallel implementations will provide a good guidance about how to materialize this advantage as software.

Changes:

Initial Announcement on mloss.org.


Showing Items 151-160 of 653 on page 16 of 66: First Previous 11 12 13 14 15 16 17 18 19 20 21 Next Last