[R] Accept CSR data for predictions (#7615)
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@@ -162,7 +162,11 @@ xgb.Booster.complete <- function(object, saveraw = TRUE) {
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#' Predicted values based on either xgboost model or model handle object.
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#'
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#' @param object Object of class \code{xgb.Booster} or \code{xgb.Booster.handle}
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#' @param newdata takes \code{matrix}, \code{dgCMatrix}, local data file or \code{xgb.DMatrix}.
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#' @param newdata takes \code{matrix}, \code{dgCMatrix}, \code{dgRMatrix}, \code{dsparseVector},
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#' local data file or \code{xgb.DMatrix}.
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#'
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#' For single-row predictions on sparse data, it's recommended to use CSR format. If passing
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#' a sparse vector, it will take it as a row vector.
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#' @param missing Missing is only used when input is dense matrix. Pick a float value that represents
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#' missing values in data (e.g., sometimes 0 or some other extreme value is used).
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#' @param outputmargin whether the prediction should be returned in the for of original untransformed
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@@ -4,8 +4,10 @@
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#' Supported input file formats are either a LIBSVM text file or a binary file that was created previously by
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#' \code{\link{xgb.DMatrix.save}}).
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#'
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#' @param data a \code{matrix} object (either numeric or integer), a \code{dgCMatrix} object, or a character
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#' string representing a filename.
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#' @param data a \code{matrix} object (either numeric or integer), a \code{dgCMatrix} object,
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#' a \code{dgRMatrix} object (only when making predictions from a fitted model),
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#' a \code{dsparseVector} object (only when making predictions from a fitted model, will be
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#' interpreted as a row vector), or a character string representing a filename.
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#' @param info a named list of additional information to store in the \code{xgb.DMatrix} object.
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#' See \code{\link{setinfo}} for the specific allowed kinds of
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#' @param missing a float value to represents missing values in data (used only when input is a dense matrix).
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@@ -37,6 +39,17 @@ xgb.DMatrix <- function(data, info = list(), missing = NA, silent = FALSE, nthre
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XGDMatrixCreateFromCSC_R, data@p, data@i, data@x, nrow(data), as.integer(NVL(nthread, -1))
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)
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cnames <- colnames(data)
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} else if (inherits(data, "dgRMatrix")) {
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handle <- .Call(
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XGDMatrixCreateFromCSR_R, data@p, data@j, data@x, ncol(data), as.integer(NVL(nthread, -1))
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)
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cnames <- colnames(data)
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} else if (inherits(data, "dsparseVector")) {
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indptr <- c(0L, as.integer(length(data@i)))
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ind <- as.integer(data@i) - 1L
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handle <- .Call(
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XGDMatrixCreateFromCSR_R, indptr, ind, data@x, length(data), as.integer(NVL(nthread, -1))
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)
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} else {
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stop("xgb.DMatrix does not support construction from ", typeof(data))
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}
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