fix some warning in Cran check
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@ -52,13 +52,13 @@ xgb.dump <- function(model = NULL, fname = NULL, fmap = "", with.stats=FALSE) {
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dt <- fread(paste(longString, collapse = ""), sep = "\n", header = F)
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dt <- fread(paste(longString, collapse = ""), sep = "\n", header = F)
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setnames(dt, "Content")
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setnames(dt, "Lines")
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if(is.null(fname)) {
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if(is.null(fname)) {
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result <- dt[Content != "0"][,Content := str_replace(Content, "^\t+", "")][Content != ""][,paste(Content)]
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result <- dt[Lines != "0"][, Lines := str_replace(Lines, "^\t+", "")][Lines != ""][, paste(Lines)]
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return(result)
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return(result)
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} else {
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} else {
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result <- dt[Content != "0"][Content != ""][,paste(Content)] %>% writeLines(fname)
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result <- dt[Lines != "0"][Lines != ""][, paste(Lines)] %>% writeLines(fname)
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return(TRUE)
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return(TRUE)
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}
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}
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}
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}
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@ -66,4 +66,4 @@ xgb.dump <- function(model = NULL, fname = NULL, fmap = "", with.stats=FALSE) {
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# Avoid error messages during CRAN check.
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# Avoid error messages during CRAN check.
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# The reason is that these variables are never declared
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# The reason is that these variables are never declared
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# They are mainly column names inferred by Data.table...
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# They are mainly column names inferred by Data.table...
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globalVariables(".")
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globalVariables(c("Lines", "."))
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27
R-package/man/xgb.save.raw.Rd
Normal file
27
R-package/man/xgb.save.raw.Rd
Normal file
@ -0,0 +1,27 @@
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% Generated by roxygen2 (4.1.0): do not edit by hand
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% Please edit documentation in R/xgb.save.raw.R
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\name{xgb.save.raw}
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\alias{xgb.save.raw}
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\title{Save xgboost model to R's raw vector,
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user can call xgb.load to load the model back from raw vector}
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\usage{
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xgb.save.raw(model)
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}
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\arguments{
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\item{model}{the model object.}
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}
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\description{
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Save xgboost model from xgboost or xgb.train
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}
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\examples{
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data(agaricus.train, package='xgboost')
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data(agaricus.test, package='xgboost')
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train <- agaricus.train
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test <- agaricus.test
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bst <- xgboost(data = train$data, label = train$label, max.depth = 2,
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eta = 1, nround = 2,objective = "binary:logistic")
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raw <- xgb.save(bst)
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bst <- xgb.load(raw)
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pred <- predict(bst, test$data)
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}
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