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add new parameters to several functions avoid the need of a text dump

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El Potaeto
2015-01-11 03:06:41 +01:00
parent 70df227689
commit c8c5789efd
5 changed files with 48 additions and 21 deletions
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7
R-package/man/xgb.importance.Rd
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@@ -4,12 +4,14 @@
\alias{xgb.importance}
\title{Show importance of features in a model}
\usage{
xgb.importance(feature_names = NULL, filename_dump = NULL)
xgb.importance(feature_names = NULL, filename_dump = NULL, model = NULL)
}
\arguments{
\item{feature_names}{names of each feature as a character vector. Can be extracted from a sparse matrix (see example). If model dump already contains feature names, this argument should be \code{NULL}.}
\item{filename_dump}{the path to the text file storing the model. Model dump must include the gain per feature and per tree (\code{with.stats = T} in function \code{xgb.dump}).}
\item{model}{generated by the \code{xgb.train} function. Avoid the creation of a dump file.}
}
\value{
A \code{data.table} of the features used in the model with their average gain (and their weight for boosted tree model) in the model.
@@ -43,9 +45,8 @@ test <- agaricus.test
bst <- xgboost(data = train$data, label = train$label, max.depth = 2,
eta = 1, nround = 2,objective = "binary:logistic")
xgb.dump(bst, 'xgb.model.dump', with.stats = T)
#agaricus.test$data@Dimnames[[2]] represents the column names of the sparse matrix.
xgb.importance(agaricus.test$data@Dimnames[[2]], 'xgb.model.dump')
xgb.importance(agaricus.test$data@Dimnames[[2]], model = bst)
}