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#' Project all trees on one tree and plot it
#'
#' Visualization of the ensemble of trees as a single collective unit.
#'
#' @param model produced by the \code{xgb.train} function.
#' @param feature_names names of each feature as a \code{character} vector.
#' @param features_keep number of features to keep in each position of the multi trees.
#' @param plot_width width in pixels of the graph to produce
#' @param plot_height height in pixels of the graph to produce
#' @param render a logical flag for whether the graph should be rendered (see Value).
#' @param ... currently not used
#'
#' @details
#'
#' This function tries to capture the complexity of a gradient boosted tree model
#' in a cohesive way by compressing an ensemble of trees into a single tree-graph representation.
#' The goal is to improve the interpretability of a model generally seen as black box.
#'
#' Note: this function is applicable to tree booster-based models only.
#'
#' It takes advantage of the fact that the shape of a binary tree is only defined by
#' its depth (therefore, in a boosting model, all trees have similar shape).
#'
#' Moreover, the trees tend to reuse the same features.
#'
#' The function projects each tree onto one, and keeps for each position the
#' \code{features_keep} first features (based on the Gain per feature measure).
#'
#' This function is inspired by this blog post:
#' \url{https://wellecks.wordpress.com/2015/02/21/peering-into-the-black-box-visualizing-lambdamart/}
#'
#' @return
#'
#' When \code{render = TRUE}:
#' returns a rendered graph object which is an \code{htmlwidget} of class \code{grViz}.
#' Similar to ggplot objects, it needs to be printed to see it when not running from command line.
#'
#' When \code{render = FALSE}:
#' silently returns a graph object which is of DiagrammeR's class \code{dgr_graph}.
#' This could be useful if one wants to modify some of the graph attributes
#' before rendering the graph with \code{\link[DiagrammeR]{render_graph}}.
#'
#' @examples
#'
#' data(agaricus.train, package='xgboost')
#'
#' bst <- xgboost(data = agaricus.train$data, label = agaricus.train$label, max_depth = 15,
#' eta = 1, nthread = 2, nrounds = 30, objective = "binary:logistic",
#' min_child_weight = 50, verbose = 0)
#'
#' p <- xgb.plot.multi.trees(model = bst, features_keep = 3)
#' print(p)
#'
#' \dontrun{
#' # Below is an example of how to save this plot to a file.
#' # Note that for `export_graph` to work, the DiagrammeRsvg and rsvg packages must also be installed.
#' library(DiagrammeR)
#' gr <- xgb.plot.multi.trees(model=bst, features_keep = 3, render=FALSE)
#' export_graph(gr, 'tree.pdf', width=1500, height=600)
#' }
#'
#' @export
xgb.plot.multi.trees <- function(model, feature_names = NULL, features_keep = 5, plot_width = NULL, plot_height = NULL,
render = TRUE, ...){
check.deprecation(...)
tree.matrix <- xgb.model.dt.tree(feature_names = feature_names, model = model)
# first number of the path represents the tree, then the following numbers are related to the path to follow
# root init
root.nodes <- tree.matrix[stri_detect_regex(ID, "\\d+-0"), ID]
tree.matrix[ID %in% root.nodes, abs.node.position := root.nodes]
precedent.nodes <- root.nodes
while (tree.matrix[, sum(is.na(abs.node.position))] > 0) {
yes.row.nodes <- tree.matrix[abs.node.position %in% precedent.nodes & !is.na(Yes)]
no.row.nodes <- tree.matrix[abs.node.position %in% precedent.nodes & !is.na(No)]
yes.nodes.abs.pos <- yes.row.nodes[, abs.node.position] %>% paste0("_0")
no.nodes.abs.pos <- no.row.nodes[, abs.node.position] %>% paste0("_1")
tree.matrix[ID %in% yes.row.nodes[, Yes], abs.node.position := yes.nodes.abs.pos]
tree.matrix[ID %in% no.row.nodes[, No], abs.node.position := no.nodes.abs.pos]
precedent.nodes <- c(yes.nodes.abs.pos, no.nodes.abs.pos)
}
tree.matrix[!is.na(Yes), Yes := paste0(abs.node.position, "_0")]
tree.matrix[!is.na(No), No := paste0(abs.node.position, "_1")]
remove.tree <- . %>% stri_replace_first_regex(pattern = "^\\d+-", replacement = "")
tree.matrix[, `:=`(abs.node.position = remove.tree(abs.node.position),
Yes = remove.tree(Yes),
No = remove.tree(No))]
nodes.dt <- tree.matrix[
, .(Quality = sum(Quality))
, by = .(abs.node.position, Feature)
][, .(Text = paste0(Feature[1:min(length(Feature), features_keep)],
" (",
format(Quality[1:min(length(Quality), features_keep)], digits = 5),
")") %>%
paste0(collapse = "\n"))
, by = abs.node.position]
edges.dt <- tree.matrix[Feature != "Leaf", .(abs.node.position, Yes)] %>%
list(tree.matrix[Feature != "Leaf", .(abs.node.position, No)]) %>%
rbindlist() %>%
setnames(c("From", "To")) %>%
.[, .N, .(From, To)] %>%
.[, N := NULL]
nodes <- DiagrammeR::create_node_df(
n = nrow(nodes.dt),
label = nodes.dt[, Text]
)
edges <- DiagrammeR::create_edge_df(
from = match(edges.dt[, From], nodes.dt[, abs.node.position]),
to = match(edges.dt[, To], nodes.dt[, abs.node.position]),
rel = "leading_to")
graph <- DiagrammeR::create_graph(
nodes_df = nodes,
edges_df = edges,
attr_theme = NULL
) %>%
DiagrammeR::add_global_graph_attrs(
attr_type = "graph",
attr = c("layout", "rankdir"),
value = c("dot", "LR")
) %>%
DiagrammeR::add_global_graph_attrs(
attr_type = "node",
attr = c("color", "fillcolor", "style", "shape", "fontname"),
value = c("DimGray", "beige", "filled", "rectangle", "Helvetica")
) %>%
DiagrammeR::add_global_graph_attrs(
attr_type = "edge",
attr = c("color", "arrowsize", "arrowhead", "fontname"),
value = c("DimGray", "1.5", "vee", "Helvetica"))
if (!render) return(invisible(graph))
DiagrammeR::render_graph(graph, width = plot_width, height = plot_height)
}
globalVariables(c(".N", "N", "From", "To", "Text", "Feature", "no.nodes.abs.pos",
"ID", "Yes", "No", "Tree", "yes.nodes.abs.pos", "abs.node.position"))
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