Nothing
predict.FMmodel <-
function(object, newdata, truncate=T, ...){
if(object$variables!=ncol(newdata)) stop(paste0("number of features (p=",ncol(newdata),") does not match with model (p=",object$variables,")"))
if(is.data.frame(newdata)) newdata=as.matrix(newdata)
newdata=as(newdata,"dgTMatrix")
object$traincases=newdata@Dim[1]
object$mX=cbind(newdata@i,newdata@j,newdata@x)
object$truncate=truncate
prediction=predictFM(object)
# if(!is.null(object$mean)&!is.null(object$sd)) prediction=prediction/0.1*object$sd+object$mean
return(prediction)
}
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