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Update lib version dependencies (for DiagrammeR mainly)

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Fix @export tag in each R file (for Roxygen 5, otherwise it doesn't work anymore)
Regerate Roxygen doc
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2015-11-07 21:01:28 +01:00
parent 635645c650
commit 0052b193cf
36 changed files with 123 additions and 126 deletions
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20
R-package/man/xgb.cv.Rd
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@@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/xgb.cv.R
\name{xgb.cv}
\alias{xgb.cv}
@@ -40,7 +40,7 @@ value that represents missing value. Sometime a data use 0 or other extreme valu
\item{showsd}{\code{boolean}, whether show standard deviation of cross validation}
\item{metrics,}{list of evaluation metrics to be used in corss validation,
\item{metrics, }{list of evaluation metrics to be used in corss validation,
when it is not specified, the evaluation metric is chosen according to objective function.
Possible options are:
\itemize{
@@ -51,11 +51,11 @@ value that represents missing value. Sometime a data use 0 or other extreme valu
\item \code{merror} Exact matching error, used to evaluate multi-class classification
}}
\item{obj}{customized objective function. Returns gradient and second order
\item{obj}{customized objective function. Returns gradient and second order
gradient with given prediction and dtrain.}
\item{feval}{custimized evaluation function. Returns
\code{list(metric='metric-name', value='metric-value')} with given
\item{feval}{custimized evaluation function. Returns
\code{list(metric='metric-name', value='metric-value')} with given
prediction and dtrain.}
\item{stratified}{\code{boolean} whether sampling of folds should be stratified by the values of labels in \code{data}}
@@ -67,12 +67,12 @@ If folds are supplied, the nfold and stratified parameters would be ignored.}
\item{print.every.n}{Print every N progress messages when \code{verbose>0}. Default is 1 which means all messages are printed.}
\item{early.stop.round}{If \code{NULL}, the early stopping function is not triggered.
If set to an integer \code{k}, training with a validation set will stop if the performance
\item{early.stop.round}{If \code{NULL}, the early stopping function is not triggered.
If set to an integer \code{k}, training with a validation set will stop if the performance
keeps getting worse consecutively for \code{k} rounds.}
\item{maximize}{If \code{feval} and \code{early.stop.round} are set, then \code{maximize} must be set as well.
\code{maximize=TRUE} means the larger the evaluation score the better.}
\code{maximize=TRUE} means the larger the evaluation score the better.}
\item{...}{other parameters to pass to \code{params}.}
}
@@ -89,9 +89,9 @@ If \code{prediction = FALSE}, just a \code{data.table} with each mean and standa
The cross valudation function of xgboost
}
\details{
The original sample is randomly partitioned into \code{nfold} equal size subsamples.
The original sample is randomly partitioned into \code{nfold} equal size subsamples.
Of the \code{nfold} subsamples, a single subsample is retained as the validation data for testing the model, and the remaining \code{nfold - 1} subsamples are used as training data.
Of the \code{nfold} subsamples, a single subsample is retained as the validation data for testing the model, and the remaining \code{nfold - 1} subsamples are used as training data.
The cross-validation process is then repeated \code{nrounds} times, with each of the \code{nfold} subsamples used exactly once as the validation data.