46 lines
1.6 KiB
R
46 lines
1.6 KiB
R
#' Contruct xgb.DMatrix object
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#'
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#' Contruct xgb.DMatrix object from dense matrix, sparse matrix or local file.
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#'
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#' @param data a \code{matrix} object, a \code{dgCMatrix} object or a character
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#' indicating the data file.
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#' @param info a list of information of the xgb.DMatrix object
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#' @param missing Missing is only used when input is dense matrix, pick a float
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#' value that represents missing value. Sometime a data use 0 or other extreme value to represents missing values.
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#
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#' @param ... other information to pass to \code{info}.
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#'
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#' @examples
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#' data(agaricus.train, package='xgboost')
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#' train <- agaricus.train
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#' dtrain <- xgb.DMatrix(train$data, label=train$label)
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#' xgb.DMatrix.save(dtrain, 'xgb.DMatrix.data')
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#' dtrain <- xgb.DMatrix('xgb.DMatrix.data')
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#' @export
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#'
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xgb.DMatrix <- function(data, info = list(), missing = 0, ...) {
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if (typeof(data) == "character") {
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handle <- .Call("XGDMatrixCreateFromFile_R", data, as.integer(FALSE),
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PACKAGE = "xgboost")
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} else if (is.matrix(data)) {
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handle <- .Call("XGDMatrixCreateFromMat_R", data, missing,
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PACKAGE = "xgboost")
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} else if (class(data) == "dgCMatrix") {
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handle <- .Call("XGDMatrixCreateFromCSC_R", data@p, data@i, data@x,
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PACKAGE = "xgboost")
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} else {
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stop(paste("xgb.DMatrix: does not support to construct from ",
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typeof(data)))
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}
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dmat <- structure(handle, class = "xgb.DMatrix")
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info <- append(info, list(...))
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if (length(info) == 0)
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return(dmat)
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for (i in 1:length(info)) {
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p <- info[i]
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xgb.setinfo(dmat, names(p), p[[1]])
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}
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return(dmat)
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}
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