Nothing
###########################################################################################################
summary.intsearch<-function(object,digits = max(3, getOption("digits") - 3), verbose=TRUE, first.n=5, ...){
fit <- object
alphas <- fit$Xtrain[,1]
lambdas <- unlist(sapply(sapply(fit$model, "[", "model"), "[", "lambda"))
deviances <- fit$Ytrain
# round problems!!!! take first from the fit
# number of selected features in the models; dfs
tmp.models<-sapply(sapply(sapply(fit$model, "[", "model"), "[", "cvreg"), "[", "glmnet.fit")
n.features<-mapply( function(List, lam) List$df[which(List$lambda %in% lam)], tmp.models, lambdas)
# optimal models
#print("chose the model with min num of FS ")
opt.models <- sapply(fit$model.list, "[", "model") [fit$Ytrain == fit$fmin ]
opt.alpha <- opt.models[[1]]$alpha
opt.lambda <- opt.models[[1]]$lambda
opt.error <- fit$fmin
out <- list(info=data.frame(alpha=alphas,lambda=lambdas,deviance=deviances,n.features=n.features),
opt.alpha=opt.alpha, opt.lambda=opt.lambda, opt.error=opt.error,
opt.models=opt.models)
class(out) <- "sum.intsearch"
if(verbose){
cat("Summary interval search \n\n")
cat(paste("show the first", first.n,"out of",nrow(out$info),"entries\n"))
print(out$info[1:first.n,])
cat("\n..............................")
cat("\n\n Optimal parameters found are: \n\n")
cat(paste("alpha = ",round(out$opt.alpha,digits),
"\t",
"lambda = ",round(out$opt.lambda,digits),
"deviance = ",round(out$opt.error,digits)))
}
invisible(out)
}
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