small documentation change
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#'
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#' Read a xgboost model text dump.
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#' Can be tree or linear model (text dump of linear model are only supported in dev version of \code{Xgboost} for now).
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#' Return a data.table of the features used in the model with their average gain (and their weight for boosted tree model) in the model.
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#'
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#' @importFrom data.table data.table
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#' @importFrom magrittr %>%
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@ -11,6 +10,8 @@
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#' @param 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}.
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#' @param 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}).
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#'
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#' @return 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.
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#'
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#' @details
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#' This is the function to understand the model trained (and through your model, your data).
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#'
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@ -11,10 +11,12 @@ xgb.importance(feature_names = NULL, filename_dump = NULL)
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\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}).}
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}
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\value{
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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.
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}
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\description{
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Read a xgboost model text dump.
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Can be tree or linear model (text dump of linear model are only supported in dev version of \code{Xgboost} for now).
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Return a data.table of the features used in the model with their average gain (and their weight for boosted tree model) in the model.
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}
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\details{
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This is the function to understand the model trained (and through your model, your data).
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