add documentation for datasets
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@ -53,3 +53,58 @@ xgboost <- function(data = NULL, label = NULL, params = list(), nrounds,
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return(bst)
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return(bst)
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}
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}
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#' Training part from Mushroom Data Set
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#'
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#' This data set is originally from the Mushroom data set,
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#' UCI Machine Learning Repository.
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#'
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#' This data set includes the following fields:
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#'
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#' \itemize{
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#' \item \code{label} the label for each record
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#' \item \code{data} a sparse Matrix of \code{dgCMatrix} class, with 127 rows.
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#' }
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#'
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#'#' @references
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#' https://archive.ics.uci.edu/ml/datasets/Mushroom
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#'
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#' Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository
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#' [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California,
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#' School of Information and Computer Science.
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#'
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#' @docType data
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#' @keywords datasets
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#' @name agaricus.train
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#' @usage data(agaricus.train)
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#' @format A list containing a label vector, and a dgCMatrix object with 6513
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#' rows and 127 variables
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NULL
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#' Test part from Mushroom Data Set
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#'
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#' This data set is originally from the Mushroom data set,
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#' UCI Machine Learning Repository.
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#'
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#' This data set includes the following fields:
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#'
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#' \itemize{
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#' \item \code{label} the label for each record
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#' \item \code{data} a sparse Matrix of \code{dgCMatrix} class, with 127 rows.
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#' }
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#'
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#' @references
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#' https://archive.ics.uci.edu/ml/datasets/Mushroom
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#'
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#' Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository
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#' [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California,
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#' School of Information and Computer Science.
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#'
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#' @docType data
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#' @keywords datasets
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#' @name agaricus.test
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#' @usage data(agaricus.test)
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#' @format A list containing a label vector, and a dgCMatrix object with 1611
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#' rows and 127 variables
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NULL
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33
R-package/man/agaricus.train.Rd
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33
R-package/man/agaricus.train.Rd
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@ -0,0 +1,33 @@
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% Generated by roxygen2 (4.0.1): do not edit by hand
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\docType{data}
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\name{agaricus.train}
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\alias{agaricus.train}
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\title{Training part from Mushroom Data Set}
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\format{A list containing a label vector, and a dgCMatrix object with 6513
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rows and 127 variables}
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\usage{
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data(agaricus.train)
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}
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\description{
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This data set is originally from the Mushroom data set,
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UCI Machine Learning Repository.
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}
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\details{
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This data set includes the following fields:
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\itemize{
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\item \code{label} the label for each record
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\item \code{data} a sparse Matrix of \code{dgCMatrix} class, with 127 rows.
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}
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#'
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}
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\references{
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https://archive.ics.uci.edu/ml/datasets/Mushroom
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Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository
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[http://archive.ics.uci.edu/ml]. Irvine, CA: University of California,
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School of Information and Computer Science.
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}
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\keyword{datasets}
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@ -30,7 +30,7 @@ xgb.cv(params = list(), data, nrounds, nfold, label = NULL, showsd = TRUE,
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\item{label}{option field, when data is Matrix}
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\item{label}{option field, when data is Matrix}
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\item{showd}{boolean, whether show standard deviation of cross validation}
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\item{showsd}{boolean, whether show standard deviation of cross validation}
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\item{metrics,}{list of evaluation metrics to be used in corss validation,
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\item{metrics,}{list of evaluation metrics to be used in corss validation,
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when it is not specified, the evaluation metric is chosen according to objective function.
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when it is not specified, the evaluation metric is chosen according to objective function.
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