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Showing Items 101-110 of 542 on page 11 of 55: First Previous 6 7 8 9 10 11 12 13 14 15 16 Next Last

Logo kernlab 0.9-9

by alexis - November 2, 2009, 16:03:50 CET [ Project Homepage BibTeX Download ] 9963 views, 2046 downloads, 0 subscriptions

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About: kernlab provides kernel-based Machine Learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods kernlab [...]

Changes:

minor fixes in kcca and ksvm functions


Logo r-cran-svmpath 0.952

by r-cran-robot - February 1, 2012, 00:00:11 CET [ Project Homepage BibTeX Download ] 9797 views, 2041 downloads, 1 subscription

About: svmpath

Changes:

Fetched by r-cran-robot on 2012-02-01 00:00:11.755984


Logo LIBOCAS 0.93

by vf - June 20, 2010, 12:22:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 9488 views, 1413 downloads, 2 subscriptions

About: The library implements Optimized Cutting Plane Algorithm (OCAS) for efficient training of linear SVM classifiers from large-scale data.

Changes:

Implemented COFFIN framework which allows efficient training of invariant image classifiers via virtual examples.


Logo SVM and Kernel Methods Toolbox 0.5

by arakotom - June 10, 2008, 21:29:39 CET [ Project Homepage BibTeX Download ] 9340 views, 2196 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 HSSVM 1.0.1

by xjbean - June 8, 2010, 16:16:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 9267 views, 1849 downloads, 1 subscription

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About: HSSVM is a software for solving multi-class problem using Hyper-sphere Support Vector Machines model, implemented by Java.

Changes:
  1. From this version, the version number is normalized to hssvm1.0.1;
  2. In this version, we delete the features about running parameter searching and run-all from Ant script, that is, commands "ant search-param" and "ant run-all" which exist in previous version are no longer available, and they are replaced with commands "svm search conf" and "svm runall conf", both of them are used on Linux(or all other POSIX systems).If you want to use this program on Windows, the cygwin is required to be installed.

Logo FABIA 2.8.0

by hochreit - October 18, 2013, 10:14:57 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 9226 views, 1919 downloads, 1 subscription

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About: FABIA is a biclustering algorithm that clusters rows and columns of a matrix simultaneously. Consequently, members of a row cluster are similar to each other on a subset of columns and, analogously, members of a column cluster are similar to each other on a subset of rows. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. Applications include detection of transcriptional modules in gene expression data and identification of haplotypes/>identity by descent< consisting of rare variants obtained by next generation sequencing.

Changes:

CHANGES IN VERSION 2.8.0

NEW FEATURES

o rescaling of lapla
o extractPlot does not plot sorted matrices

CHANGES IN VERSION 2.4.0

o spfabia bugfixes

CHANGES IN VERSION 2.3.1

NEW FEATURES

o Getters and setters for class Factorization

2.0.0:

  • spfabia: fabia for a sparse data matrix (in sparse matrix format) and sparse vector/matrix computations in the code to speed up computations. spfabia applications: (a) detecting >identity by descent< in next generation sequencing data with rare variants, (b) detecting >shared haplotypes< in disease studies based on next generation sequencing data with rare variants;
  • fabia for non-negative factorization (parameter: non_negative);
  • changed to C and removed dependencies to Rcpp;
  • improved update for lambda (alpha should be smaller, e.g. 0.03);
  • introduced maximal number of row elements (lL);
  • introduced cycle bL when upper bounds nL or lL are effective;
  • reduced computational complexity;
  • bug fixes: (a) update formula for lambda: tighter approximation, (b) corrected inverse of the conditional covariance matrix of z;

1.4.0:

  • New option nL: maximal number of biclusters per row element;
  • Sort biclusters according to information content;
  • Improved and extended preprocessing;
  • Update to R2.13

Logo KeplerWeka 20101008

by fracpete - October 9, 2010, 05:27:13 CET [ Project Homepage BibTeX Download ] 9183 views, 3133 downloads, 1 subscription

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

Changes:
  • Now compatible with Kepler 2.0
  • New version of WEKA included (patched 3.7.2 release), WEKA's new package manager works in conjunction with Kepler
  • Renamed actor Count to ConditionalTee, introduced new Count actor
  • Removed actors OutputLogger, MultiSync, TwinSync

Logo r-cran-VR 7.2-49

by r-cran-robot - September 25, 2009, 00:00:00 CET [ Project Homepage BibTeX Download ] 9107 views, 2340 downloads, 1 subscription

About: VR

Changes:

Fetched by r-cran-robot on 2009-10-03 07:16:05.643423


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 ] 9092 views, 1348 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 SimpleMKL 0.5

by arakotom - June 11, 2008, 00:56:47 CET [ Project Homepage BibTeX Download ] 8944 views, 2280 downloads, 5 subscriptions

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About: Matlab Multiple Kernel Learning toolbox. Features : MKL for SVM Classification, Regression and MultiClass. It needs SVM-KM Toolbox

Changes:

Initial Announcement on mloss.org.


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