Nothing
msr.elnet <- function(ms, nfolds = 10)
{
buildlm <- function(ms, nfolds){
nc <- ncol(ms$x)
nr <- nrow(ms$x)
lms <- vector("list", length(ms$mins))
df <- data.frame(y=ms$y, ms$x)
if(length(ms$crystalsSize) == 1) {
df <- data.frame(y = ms$y, ms$x)
f <- formula(y ~ 0+.) #glment adds an intercept
mm <- model.matrix(f, df);
}
else{
df <- data.frame(y = ms$y, ms$x, cID = as.factor(ms$crystals))
f <- formula(y ~ 0+. + .:cID) #glment adds an intercept
mm <- model.matrix(f, df);
}
obj <- cv.glmnet(y = ms$y, x = mm, nfolds = nfolds, standardize = FALSE)
obj
}
buildslm <- function(ms, nfolds){
obj <- structure(list(ms = ms), class = "msr")
mm <- model.matrix(obj, ms$x)
slm <- cv.glmnet(y = ms$y, x = mm, nfolds = nfolds, standardize = FALSE)
slm
}
if(is.null(ms$nLevels)){
l <- buildlm(ms, nfolds)
if(class(ms) == "msc.svm"){
if( ! is.null(ms$svm) ){
df <- data.frame(cry = as.factor(ms$crystals), obj$x)
ms$svm <- svm(cry ~ ., df, probability=TRUE, cost=ms$cost, scale = FALSE)
}
}
obj <- structure(list(ms = ms, lm = l, slm = buildslm(ms, nfolds)), class = "msr.elnet")
}
else{
lms <- c()
minCV <- Inf
pLevel <- 0
for(i in 1:ms$nLevels){
lms[[i]] <- buildlm(ms$mscl[[i]], nfolds)
cv <- min(lms[[i]]$cvm)
if(minCV > cv){
minBIC <- cv
pLevel <- i
}
}
if(class(ms) == "msc.svm"){
if( ! is.null(ms$mscl[[pLevel]]$svm) ){
df <- data.frame(cry = as.factor(ms$mscl[[pLevel]]$crystals), obj$mscl[[pLevel]]$x)
ms$mscl[[pLevel]]$svm <- svm(cry ~ ., df, probability=TRUE, cost=ms$cost, scale = FALSE)
}
}
slm <- buildslm(ms$mscl[[pLevel]], nfolds)
obj <- structure(list(ms = ms, lms = lms, slm= slm, predictLevel = pLevel), class = "msr.elnet")
}
obj
}
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