56 lines
2.0 KiB
R
56 lines
2.0 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/xgb.plot.shap.R
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\name{xgb.shap.data}
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\alias{xgb.shap.data}
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\title{Prepare data for SHAP plots. To be used in xgb.plot.shap, xgb.plot.shap.summary, etc.
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Internal utility function.}
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\usage{
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xgb.shap.data(
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data,
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shap_contrib = NULL,
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features = NULL,
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top_n = 1,
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model = NULL,
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trees = NULL,
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target_class = NULL,
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approxcontrib = FALSE,
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subsample = NULL,
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max_observations = 1e+05
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)
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}
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\arguments{
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\item{data}{data as a \code{matrix} or \code{dgCMatrix}.}
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\item{shap_contrib}{a matrix of SHAP contributions that was computed earlier for the above
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\code{data}. When it is NULL, it is computed internally using \code{model} and \code{data}.}
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\item{features}{a vector of either column indices or of feature names to plot. When it is NULL,
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feature importance is calculated, and \code{top_n} high ranked features are taken.}
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\item{top_n}{when \code{features} is NULL, top_n [1, 100] most important features in a model are taken.}
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\item{model}{an \code{xgb.Booster} model. It has to be provided when either \code{shap_contrib}
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or \code{features} is missing.}
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\item{trees}{passed to \code{\link{xgb.importance}} when \code{features = NULL}.}
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\item{target_class}{is only relevant for multiclass models. When it is set to a 0-based class index,
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only SHAP contributions for that specific class are used.
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If it is not set, SHAP importances are averaged over all classes.}
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\item{approxcontrib}{passed to \code{\link{predict.xgb.Booster}} when \code{shap_contrib = NULL}.}
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\item{subsample}{a random fraction of data points to use for plotting. When it is NULL,
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it is set so that up to 100K data points are used.}
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}
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\value{
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A list containing: 'data', a matrix containing sample observations
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and their feature values; 'shap_contrib', a matrix containing the SHAP contribution
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values for these observations.
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}
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\description{
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Prepare data for SHAP plots. To be used in xgb.plot.shap, xgb.plot.shap.summary, etc.
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Internal utility function.
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}
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\keyword{internal}
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