predict.lognet=function(object,newx,s=NULL,type=c("link","response","coefficients","class","nonzero"),exact=FALSE,offset,...){
type=match.arg(type)
### remember that although the fortran lognet makes predictions
### for the first class, we make predictions for the second class
### to avoid confusion with 0/1 responses.
### glmnet flipped the signs of the coefficients
nfit=NextMethod("predict")
switch(type,
response={
pp=exp(-nfit)
1/(1+pp)
},
class={
cnum=ifelse(nfit>0,2,1)
clet=object$classnames[cnum]
if(is.matrix(cnum))clet=array(clet,dim(cnum),dimnames(cnum))
clet
},
nfit
)
}
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