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# Author: Babak Naimi, naimi.b@gmail.com
# Date : March. 2016
# last update: July 2017
# Version 1.2
# Licence GPL v3
#-------------
methodInfo <- list(name=c('glmnet','GLMNET','glmelastic','glmlasso'),
packages='glmnet',
modelTypes = c('pa','pb','ab','n'),
fitParams = list(formula='standard.formula',data='sdmDataFrame'),
fitSettings = list(family='binomial',alpha=1),
fitFunction = function(formula,data,family,...) {
x <- .getData.sdmMatrix(formula,data)
y <- .getData.sdmY(formula,data)
if (family == 'binomial') m <- cv.glmnet(x,y,family="binomial",type.measure = 'auc')
else m <- cv.glmnet(x,y,family=family)
glmnet(x=x,y=y,family=family,lambda=m$lambda.1se,...)
},
settingRules = function(x='sdmVariables',f='fitSettings') {
if (x@distribution %in% c('poisson','multinomial')) {
f[['family']] <- x@distribution
}
list(fitSettings=f)
},
tuneParams = NULL,
predictParams=list(object='model',formula='standard.formula',newx='sdmDataFrame'),
predictSettings=list(type='response'),
predictFunction=function(object,formula,newx,type) {
newx <- .getData.sdmMatrix(formula,newx)
predict.glmnet(object,newx,type=type)[,1]
},
#------ metadata (optional):
title='GLM with lasso or elasticnet regularization',
creator='Babak Naimi',
authors=c('Jerome Friedman, Trevor Hastie, Noah Simon and Rob Tibshirani'), # authors of the main method
email='naimi.b@gmail.com',
url='http://r-gis.net',
citation=list(bibentry('Article',title = "Regularization Paths for Generalized Linear Models via Coordinate Descent,",
author = as.person("J. Friedman [aut], T. Hastie [aut], R. Tibshirani [aut]"),
year='2008',
journal = "Journal of Statistical Software",
number="33/1",
pages="1-22"
)
),
description="Fit a generalized linear model via penalized maximum likelihood. The regularization path is computed for the lasso or elasticnet penalty at a grid of values for the regularization parameter lambda."
)
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