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[R-package] JSON dump format and a couple of bugfixes (#1855)

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* [R-package] JSON tree dump interface

* [R-package] precision bugfix in xgb.attributes

* [R-package] bugfix for cb.early.stop called from xgb.cv

* [R-package] a bit more clarity on labels checking in xgb.cv

* [R-package] test JSON dump for gblinear as well

* whitespace lint
This commit is contained in:
Vadim Khotilovich
2016-12-11 12:48:39 -06:00
committed by Tianqi Chen
parent 0268dedeea
commit b21e658a02
10 changed files with 72 additions and 22 deletions
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11
R-package/R/xgb.cv.R
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@@ -16,10 +16,10 @@
#'
#' See \code{\link{xgb.train}} for further details.
#' See also demo/ for walkthrough example in R.
#' @param data takes an \code{xgb.DMatrix} or \code{Matrix} as the input.
#' @param data takes an \code{xgb.DMatrix}, \code{matrix}, or \code{dgCMatrix} as the input.
#' @param nrounds the max number of iterations
#' @param nfold the original dataset is randomly partitioned into \code{nfold} equal size subsamples.
#' @param label vector of response values. Should be provided only when data is \code{DMatrix}.
#' @param label vector of response values. Should be provided only when data is an R-matrix.
#' @param missing is only used when input is a dense matrix. By default is set to NA, which means
#' that NA values should be considered as 'missing' by the algorithm.
#' Sometimes, 0 or other extreme value might be used to represent missing values.
@@ -129,10 +129,9 @@ xgb.cv <- function(params=list(), data, nrounds, nfold, label = NULL, missing =
#if (is.null(params[['eval_metric']]) && is.null(feval))
# stop("Either 'eval_metric' or 'feval' must be provided for CV")
# Labels
if (class(data) == 'xgb.DMatrix')
labels <- getinfo(data, 'label')
if (is.null(labels))
# Check the labels
if ( (class(data) == 'xgb.DMatrix' && is.null(getinfo(data, 'label'))) ||
(class(data) != 'xgb.DMatrix' && is.null(label)))
stop("Labels must be provided for CV either through xgb.DMatrix, or through 'label=' when 'data' is matrix")
# CV folds