Plot model trees deepness
Visualizes distributions related to depth of tree leafs.
xgb.plot.deepness uses base R graphics, while xgb.ggplot.deepness uses the ggplot backend.
xgb.ggplot.deepness(
model = NULL,
which = c("2x1", "max.depth", "med.depth", "med.weight")
)
xgb.plot.deepness(
model = NULL,
which = c("2x1", "max.depth", "med.depth", "med.weight"),
plot = TRUE,
...
)model |
either an |
which |
which distribution to plot (see details). |
plot |
(base R barplot) whether a barplot should be produced. If FALSE, only a data.table is returned. |
... |
other parameters passed to |
When which="2x1", two distributions with respect to the leaf depth
are plotted on top of each other:
the distribution of the number of leafs in a tree model at a certain depth;
the distribution of average weighted number of observations ("cover") ending up in leafs at certain depth.
Those could be helpful in determining sensible ranges of the max_depth
and min_child_weight parameters.
When which="max.depth" or which="med.depth", plots of either maximum or median depth
per tree with respect to tree number are created. And which="med.weight" allows to see how
a tree's median absolute leaf weight changes through the iterations.
This function was inspired by the blog post https://github.com/aysent/random-forest-leaf-visualization.
Other than producing plots (when plot=TRUE), the xgb.plot.deepness function
silently returns a processed data.table where each row corresponds to a terminal leaf in a tree model,
and contains information about leaf's depth, cover, and weight (which is used in calculating predictions).
The xgb.ggplot.deepness silently returns either a list of two ggplot graphs when which="2x1"
or a single ggplot graph for the other which options.
data(agaricus.train, package='xgboost')
# Change max_depth to a higher number to get a more significant result
bst <- xgboost(data = agaricus.train$data, label = agaricus.train$label, max_depth = 6,
eta = 0.1, nthread = 2, nrounds = 50, objective = "binary:logistic",
subsample = 0.5, min_child_weight = 2)
xgb.plot.deepness(bst)
xgb.ggplot.deepness(bst)
xgb.plot.deepness(bst, which='max.depth', pch=16, col=rgb(0,0,1,0.3), cex=2)
xgb.plot.deepness(bst, which='med.weight', pch=16, col=rgb(0,0,1,0.3), cex=2)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.