SVMMaj: SVMMaj algorithm

Implements the SVM-Maj algorithm to train data with Support Vector Machine, this algorithm uses two efficient updates, one for linear kernel and one for the nonlinear kernel.

AuthorHoksan Yip, Patrick J.F. Groenen, Georgi Nalbantov
Date of publication2011-01-13 12:09:49
MaintainerHok San Yip <hoksan@gmail.com>
LicenseGPL-2
Version0.2-2

View on CRAN

Files in this package

SVMMaj
SVMMaj/data
SVMMaj/data/AusCredit.r
SVMMaj/data/diabetes.r
SVMMaj/data/libsvm.Rdata
SVMMaj/data/voting.R
SVMMaj/DESCRIPTION
SVMMaj/man
SVMMaj/man/australian.Rd
SVMMaj/man/diabetes.rd
SVMMaj/man/hinge.Rd SVMMaj/man/ispline.Rd SVMMaj/man/normalize.Rd
SVMMaj/man/predict.svmmaj.rd
SVMMaj/man/svmmaj.Rd SVMMaj/man/svmmajcrossval.Rd SVMMaj/man/voting.Rd
SVMMaj/NAMESPACE
SVMMaj/R
SVMMaj/R/hinge.R SVMMaj/R/ispline.R SVMMaj/R/normalize.R
SVMMaj/R/roccurve.r
SVMMaj/R/svmmaj.R
SVMMaj/R/svmmaj2.r
SVMMaj/R/svmmajcrossval.R SVMMaj/R/svmmajdefault.R SVMMaj/R/svmmajtuning.R SVMMaj/R/update.R

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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