[R-package] JSON dump format and a couple of bugfixes (#1855)
* [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
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Tianqi Chen
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@@ -26,13 +26,13 @@ xgb.cv(params = list(), data, nrounds, nfold, label = NULL, missing = NA,
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See \code{\link{xgb.train}} for further details.
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See also demo/ for walkthrough example in R.}
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\item{data}{takes an \code{xgb.DMatrix} or \code{Matrix} as the input.}
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\item{data}{takes an \code{xgb.DMatrix}, \code{matrix}, or \code{dgCMatrix} as the input.}
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\item{nrounds}{the max number of iterations}
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\item{nfold}{the original dataset is randomly partitioned into \code{nfold} equal size subsamples.}
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\item{label}{vector of response values. Should be provided only when data is \code{DMatrix}.}
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\item{label}{vector of response values. Should be provided only when data is an R-matrix.}
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\item{missing}{is only used when input is a dense matrix. By default is set to NA, which means
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that NA values should be considered as 'missing' by the algorithm.
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