# Author: Babak Naimi, naimi.b@gmail.com
# Date (last update): Nov. 2021
# Version 1.3
# Licence GPL v3
#-------------
methodInfo <- list(name=c('svm','SVM','ksvm'),
packages='kernlab',
modelTypes = c('pa','pb','ab','n'),
fitParams = list(x='standard.formula',data='sdmDataFrame'),
fitSettings = list(type='C-svc',kernel='rbfdot',epsilon=0.1,prob.model=TRUE,tol=0.001,shrinking=TRUE),
fitFunction = 'ksvm',
settingRules = function(x='sdmVariables',f='fitSettings') {
if (x@distribution == 'multinomial') f[['type']] <- 'C-svc'
list(fitSettings=f)
},
tuneParams = NULL,
predictParams=list(object='model',newdata='sdmDataFrame'),
predictSettings=list(type='probabilities'),
predictFunction=function(object, newdata, type , coupler = "minpair") {
px <- predict(object,newdata,type=type,coupler=coupler)
if (ncol(px) == 2) px[,2]
else px
},
#------ metadata (optional):
title='Support Vector Machines',
creator='Babak Naimi',
authors=c('Alexandros Karatzoglou'), # authors of the main method
email='naimi.b@gmail.com',
url='http://r-gis.net',
citation=list(bibentry('Article',title = "LIBSVM: a library for Support Vector Machines",
author = as.person("C. Chih-Chung [aut], L. Chih-Jen [aut]"),
year='2015',
journal = "http://www.csie.ntu.edu.tw/~cjlin/libsvm"
)
),
description='Support Vector Machines are an excellent tool for classification, novelty detection, and regression'
)
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