e8a6597957
* [R] fix predict contributions for data with no colnames * [R] add a render parameter for xgb.plot.multi.trees; fixes #2628 * [R] update Rd's * [R] remove unnecessary dep-package from R cmake install * silence type warnings; readability * [R] silence complaint about incomplete line at the end * [R] initial version of xgb.plot.shap() * [R] more work on xgb.plot.shap * [R] enforce black font in xgb.plot.tree; fixes #2640 * [R] if feature names are available, check in predict that they are the same; fixes #2857 * [R] cran check and lint fixes * remove tabs * [R] add references; a test for plot.shap
76 lines
2.8 KiB
R
76 lines
2.8 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/xgb.plot.multi.trees.R
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\name{xgb.plot.multi.trees}
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\alias{xgb.plot.multi.trees}
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\title{Project all trees on one tree and plot it}
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\usage{
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xgb.plot.multi.trees(model, feature_names = NULL, features_keep = 5,
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plot_width = NULL, plot_height = NULL, render = TRUE, ...)
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}
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\arguments{
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\item{model}{produced by the \code{xgb.train} function.}
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\item{feature_names}{names of each feature as a \code{character} vector.}
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\item{features_keep}{number of features to keep in each position of the multi trees.}
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\item{plot_width}{width in pixels of the graph to produce}
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\item{plot_height}{height in pixels of the graph to produce}
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\item{render}{a logical flag for whether the graph should be rendered (see Value).}
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\item{...}{currently not used}
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}
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\value{
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When \code{render = TRUE}:
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returns a rendered graph object which is an \code{htmlwidget} of class \code{grViz}.
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Similar to ggplot objects, it needs to be printed to see it when not running from command line.
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When \code{render = FALSE}:
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silently returns a graph object which is of DiagrammeR's class \code{dgr_graph}.
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This could be useful if one wants to modify some of the graph attributes
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before rendering the graph with \code{\link[DiagrammeR]{render_graph}}.
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}
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\description{
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Visualization of the ensemble of trees as a single collective unit.
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}
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\details{
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This function tries to capture the complexity of a gradient boosted tree model
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in a cohesive way by compressing an ensemble of trees into a single tree-graph representation.
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The goal is to improve the interpretability of a model generally seen as black box.
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Note: this function is applicable to tree booster-based models only.
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It takes advantage of the fact that the shape of a binary tree is only defined by
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its depth (therefore, in a boosting model, all trees have similar shape).
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Moreover, the trees tend to reuse the same features.
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The function projects each tree onto one, and keeps for each position the
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\code{features_keep} first features (based on the Gain per feature measure).
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This function is inspired by this blog post:
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\url{https://wellecks.wordpress.com/2015/02/21/peering-into-the-black-box-visualizing-lambdamart/}
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}
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\examples{
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data(agaricus.train, package='xgboost')
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bst <- xgboost(data = agaricus.train$data, label = agaricus.train$label, max_depth = 15,
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eta = 1, nthread = 2, nrounds = 30, objective = "binary:logistic",
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min_child_weight = 50, verbose = 0)
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p <- xgb.plot.multi.trees(model = bst, features_keep = 3)
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print(p)
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\dontrun{
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# Below is an example of how to save this plot to a file.
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# Note that for `export_graph` to work, the DiagrammeRsvg and rsvg packages must also be installed.
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library(DiagrammeR)
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gr <- xgb.plot.multi.trees(model=bst, features_keep = 3, render=FALSE)
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export_graph(gr, 'tree.pdf', width=1500, height=600)
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}
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}
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