75 lines
2.9 KiB
R
75 lines
2.9 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/xgb.ggplot.R, R/xgb.plot.deepness.R
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\name{xgb.ggplot.deepness}
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\alias{xgb.ggplot.deepness}
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\alias{xgb.plot.deepness}
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\title{Plot model trees deepness}
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\usage{
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xgb.ggplot.deepness(model = NULL, which = c("2x1", "max.depth", "med.depth",
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"med.weight"))
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xgb.plot.deepness(model = NULL, which = c("2x1", "max.depth", "med.depth",
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"med.weight"), plot = TRUE, ...)
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}
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\arguments{
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\item{model}{either an \code{xgb.Booster} model generated by the \code{xgb.train} function
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or a data.table result of the \code{xgb.model.dt.tree} function.}
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\item{which}{which distribution to plot (see details).}
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\item{plot}{(base R barplot) whether a barplot should be produced.
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If FALSE, only a data.table is returned.}
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\item{...}{other parameters passed to \code{barplot} or \code{plot}.}
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}
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\value{
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Other than producing plots (when \code{plot=TRUE}), the \code{xgb.plot.deepness} function
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silently returns a processed data.table where each row corresponds to a terminal leaf in a tree model,
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and contains information about leaf's depth, cover, and weight (which is used in calculating predictions).
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The \code{xgb.ggplot.deepness} silently returns either a list of two ggplot graphs when \code{which="2x1"}
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or a single ggplot graph for the other \code{which} options.
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}
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\description{
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Visualizes distributions related to depth of tree leafs.
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\code{xgb.plot.deepness} uses base R graphics, while \code{xgb.ggplot.deepness} uses the ggplot backend.
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}
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\details{
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When \code{which="2x1"}, two distributions with respect to the leaf depth
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are plotted on top of each other:
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\itemize{
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\item the distribution of the number of leafs in a tree model at a certain depth;
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\item the distribution of average weighted number of observations ("cover")
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ending up in leafs at certain depth.
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}
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Those could be helpful in determining sensible ranges of the \code{max_depth}
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and \code{min_child_weight} parameters.
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When \code{which="max.depth"} or \code{which="med.depth"}, plots of either maximum or median depth
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per tree with respect to tree number are created. And \code{which="med.weight"} allows to see how
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a tree's median absolute leaf weight changes through the iterations.
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This function was inspired by the blog post
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\url{https://github.com/aysent/random-forest-leaf-visualization}.
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}
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\examples{
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data(agaricus.train, package='xgboost')
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# Change max_depth to a higher number to get a more significant result
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bst <- xgboost(data = agaricus.train$data, label = agaricus.train$label, max_depth = 6,
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eta = 0.1, nthread = 2, nrounds = 50, objective = "binary:logistic",
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subsample = 0.5, min_child_weight = 2)
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xgb.plot.deepness(bst)
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xgb.ggplot.deepness(bst)
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xgb.plot.deepness(bst, which='max.depth', pch=16, col=rgb(0,0,1,0.3), cex=2)
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xgb.plot.deepness(bst, which='med.weight', pch=16, col=rgb(0,0,1,0.3), cex=2)
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}
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\seealso{
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\code{\link{xgb.train}}, \code{\link{xgb.model.dt.tree}}.
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}
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