Fix loading old logit model, helper for converting old pickle. (#5281)
* Fix loading old logit model. * Add a helper script for converting old pickle file. * Add version as a model parameter. * Remove the size check in R test to relax the size constraint. * Add missing R doc for passing linting. Run devtools. * Cleanup old model IO logic. * Test compatibility on CI. * Make the argument as required.
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@@ -4,7 +4,7 @@
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\name{agaricus.test}
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\alias{agaricus.test}
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\title{Test part from Mushroom Data Set}
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\format{A list containing a label vector, and a dgCMatrix object with 1611
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\format{A list containing a label vector, and a dgCMatrix object with 1611
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rows and 126 variables}
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\usage{
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data(agaricus.test)
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@@ -24,8 +24,8 @@ This data set includes the following fields:
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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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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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@@ -4,7 +4,7 @@
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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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\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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@@ -24,8 +24,8 @@ This data set includes the following fields:
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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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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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@@ -49,6 +49,9 @@ It will use all the trees by default (\code{NULL} value).}
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prediction outputs per case. This option has no effect when either of predleaf, predcontrib,
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or predinteraction flags is TRUE.}
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\item{training}{whether is the prediction result used for training. For dart booster,
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training predicting will perform dropout.}
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\item{...}{Parameters passed to \code{predict.xgb.Booster}}
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}
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\value{
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