Merge pull request #198 from pommedeterresautee/master
Add new nrow function for xgb.DMatrix + small function doc changes
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adfa023822
@ -16,6 +16,7 @@ export(xgb.save)
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export(xgb.save.raw)
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export(xgb.train)
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export(xgboost)
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exportMethods(nrow)
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exportMethods(predict)
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import(methods)
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importClassesFrom(Matrix,dgCMatrix)
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@ -52,4 +53,3 @@ importFrom(stringr,str_match)
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importFrom(stringr,str_replace)
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importFrom(stringr,str_split)
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importFrom(stringr,str_trim)
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import(vcd)
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@ -4,6 +4,15 @@ setClass('xgb.DMatrix')
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#'
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#' Get information of an xgb.DMatrix object
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#'
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#' The information can be one of the following:
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#'
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#' \itemize{
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#' \item \code{label}: label Xgboost learn from ;
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#' \item \code{weight}: to do a weight rescale ;
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#' \item \code{base_margin}: base margin is the base prediction Xgboost will boost from ;
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#' \item \code{nrow}: number of rows of the \code{xgb.DMatrix}.
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#' }
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#'
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#' @examples
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#' data(agaricus.train, package='xgboost')
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#' train <- agaricus.train
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@ -19,7 +28,9 @@ getinfo <- function(object, ...){
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UseMethod("getinfo")
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}
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#' @param object Object of class "xgb.DMatrix"
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#' @param object Object of class \code{xgb.DMatrix}
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#' @param name the name of the field to get
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#' @param ... other parameters
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#' @rdname getinfo
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19
R-package/R/nrow.xgb.DMatrix.R
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19
R-package/R/nrow.xgb.DMatrix.R
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@ -0,0 +1,19 @@
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setGeneric("nrow")
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#' @title Number of xgb.DMatrix rows
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#' @description \code{nrow} return the number of rows present in the \code{xgb.DMatrix}.
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#' @param x Object of class \code{xgb.DMatrix}
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#'
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#' @examples
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#' data(agaricus.train, package='xgboost')
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#' train <- agaricus.train
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#' dtrain <- xgb.DMatrix(train$data, label=train$label)
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#' stopifnot(nrow(dtrain) == nrow(train$data))
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#'
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#' @export
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setMethod("nrow",
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signature = "xgb.DMatrix",
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definition = function(x) {
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xgb.numrow(x)
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}
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)
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@ -2,6 +2,15 @@
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#'
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#' Set information of an xgb.DMatrix object
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#'
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#' It can be one of the following:
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#'
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#' \itemize{
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#' \item \code{label}: label Xgboost learn from ;
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#' \item \code{weight}: to do a weight rescale ;
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#' \item \code{base_margin}: base margin is the base prediction Xgboost will boost from ;
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#' \item \code{group}.
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#' }
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#'
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#' @examples
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#' data(agaricus.train, package='xgboost')
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#' train <- agaricus.train
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@ -45,7 +45,7 @@
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#' train <- agaricus.train
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#' test <- agaricus.test
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#' bst <- xgboost(data = train$data, label = train$label, max.depth = 2,
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#' eta = 1, nthread = 2, nround = 2,objective = "binary:logistic")
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#' eta = 1, nthread = 2, nround = 2, objective = "binary:logistic")
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#' pred <- predict(bst, test$data)
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#'
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#' @export
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@ -11,7 +11,7 @@ getinfo(object, ...)
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\S4method{getinfo}{xgb.DMatrix}(object, name)
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}
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\arguments{
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\item{object}{Object of class "xgb.DMatrix"}
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\item{object}{Object of class \code{xgb.DMatrix}}
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\item{...}{other parameters}
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@ -20,6 +20,16 @@ getinfo(object, ...)
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\description{
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Get information of an xgb.DMatrix object
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}
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\details{
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The information can be one of the following:
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\itemize{
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\item \code{label}: label Xgboost learn from ;
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\item \code{weight}: to do a weight rescale ;
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\item \code{base_margin}: base margin is the base prediction Xgboost will boost from ;
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\item \code{nrow}: number of rows of the \code{xgb.DMatrix}.
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}
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}
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\examples{
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data(agaricus.train, package='xgboost')
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train <- agaricus.train
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22
R-package/man/nrow-xgb.DMatrix-method.Rd
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22
R-package/man/nrow-xgb.DMatrix-method.Rd
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@ -0,0 +1,22 @@
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% Generated by roxygen2 (4.1.0): do not edit by hand
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% Please edit documentation in R/nrow.xgb.DMatrix.R
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\docType{methods}
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\name{nrow,xgb.DMatrix-method}
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\alias{nrow,xgb.DMatrix-method}
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\title{Number of xgb.DMatrix rows}
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\usage{
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\S4method{nrow}{xgb.DMatrix}(x)
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}
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\arguments{
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\item{x}{Object of class \code{xgb.DMatrix}}
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}
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\description{
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\code{nrow} return the number of rows present in the \code{xgb.DMatrix}.
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}
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\examples{
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data(agaricus.train, package='xgboost')
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train <- agaricus.train
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dtrain <- xgb.DMatrix(train$data, label=train$label)
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stopifnot(nrow(dtrain) == nrow(train$data))
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}
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@ -22,6 +22,16 @@ setinfo(object, ...)
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\description{
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Set information of an xgb.DMatrix object
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}
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\details{
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It can be one of the following:
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\itemize{
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\item \code{label}: label Xgboost learn from ;
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\item \code{weight}: to do a weight rescale ;
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\item \code{base_margin}: base margin is the base prediction Xgboost will boost from ;
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\item \code{group}.
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}
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}
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\examples{
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data(agaricus.train, package='xgboost')
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train <- agaricus.train
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@ -59,7 +59,7 @@ data(agaricus.test, package='xgboost')
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train <- agaricus.train
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test <- agaricus.test
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bst <- xgboost(data = train$data, label = train$label, max.depth = 2,
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eta = 1, nthread = 2, nround = 2,objective = "binary:logistic")
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eta = 1, nthread = 2, nround = 2, objective = "binary:logistic")
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pred <- predict(bst, test$data)
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}
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