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Merge model compatibility fixes from 1.0rc branch. (#5305)

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* Port test model compatibility.
* Port logit model fix.

https://github.com/dmlc/xgboost/pull/5248
https://github.com/dmlc/xgboost/pull/5281
This commit is contained in:
Jiaming Yuan
2020-02-13 20:41:59 +08:00
committed by GitHub
parent 29eeea709a
commit 911a902835
19 changed files with 550 additions and 106 deletions
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2
R-package/R/xgb.Booster.R
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@@ -139,6 +139,8 @@ xgb.Booster.complete <- function(object, saveraw = TRUE) {
#' @param reshape whether to reshape the vector of predictions to a matrix form when there are several
#' prediction outputs per case. This option has no effect when either of predleaf, predcontrib,
#' or predinteraction flags is TRUE.
#' @param training whether is the prediction result used for training. For dart booster,
#' training predicting will perform dropout.
#' @param ... Parameters passed to \code{predict.xgb.Booster}
#'
#' @details

6
R-package/man/agaricus.test.Rd
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@@ -4,7 +4,7 @@
\name{agaricus.test}
\alias{agaricus.test}
\title{Test part from Mushroom Data Set}
\format{A list containing a label vector, and a dgCMatrix object with 1611
\format{A list containing a label vector, and a dgCMatrix object with 1611
rows and 126 variables}
\usage{
data(agaricus.test)
@@ -24,8 +24,8 @@ This data set includes the following fields:
\references{
https://archive.ics.uci.edu/ml/datasets/Mushroom
Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository
[http://archive.ics.uci.edu/ml]. Irvine, CA: University of California,
Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository
[http://archive.ics.uci.edu/ml]. Irvine, CA: University of California,
School of Information and Computer Science.
}
\keyword{datasets}

6
R-package/man/agaricus.train.Rd
View File

@@ -4,7 +4,7 @@
\name{agaricus.train}
\alias{agaricus.train}
\title{Training part from Mushroom Data Set}
\format{A list containing a label vector, and a dgCMatrix object with 6513
\format{A list containing a label vector, and a dgCMatrix object with 6513
rows and 127 variables}
\usage{
data(agaricus.train)
@@ -24,8 +24,8 @@ This data set includes the following fields:
\references{
https://archive.ics.uci.edu/ml/datasets/Mushroom
Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository
[http://archive.ics.uci.edu/ml]. Irvine, CA: University of California,
Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository
[http://archive.ics.uci.edu/ml]. Irvine, CA: University of California,
School of Information and Computer Science.
}
\keyword{datasets}

3
R-package/man/predict.xgb.Booster.Rd
View File

@@ -49,6 +49,9 @@ It will use all the trees by default (\code{NULL} value).}
prediction outputs per case. This option has no effect when either of predleaf, predcontrib,
or predinteraction flags is TRUE.}
\item{training}{whether is the prediction result used for training. For dart booster,
training predicting will perform dropout.}
\item{...}{Parameters passed to \code{predict.xgb.Booster}}
}
\value{

2
R-package/tests/testthat/test_custom_objective.R
View File

@@ -31,7 +31,6 @@ num_round <- 2
test_that("custom objective works", {
bst <- xgb.train(param, dtrain, num_round, watchlist)
expect_equal(class(bst), "xgb.Booster")
expect_equal(length(bst$raw), 1100)
expect_false(is.null(bst$evaluation_log))
expect_false(is.null(bst$evaluation_log$eval_error))
expect_lt(bst$evaluation_log[num_round, eval_error], 0.03)
@@ -58,5 +57,4 @@ test_that("custom objective using DMatrix attr works", {
param$objective = logregobjattr
bst <- xgb.train(param, dtrain, num_round, watchlist)
expect_equal(class(bst), "xgb.Booster")
expect_equal(length(bst$raw), 1100)
})