Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

[R] maintenance Apr 2017 (#2237)

Browse Source 
* [R] make sure things work for a single split model; fixes #2191

* [R] add option use_int_id to xgb.model.dt.tree

* [R] add example of exporting tree plot to a file

* [R] set save_period = NULL as default in xgboost() to be the same as in xgb.train; fixes #2182

* [R] it's a good practice after CRAN releases to bump up package version in dev

* [R] allow xgb.DMatrix construction from integer dense matrices

* [R] xgb.DMatrix: silent parameter; improve documentation

* [R] xgb.model.dt.tree code style changes

* [R] update NEWS with parameter changes

* [R] code safety & style; handle non-strict matrix and inherited classes of input and model; fixes #2242

* [R] change to x.y.z.p R-package versioning scheme and set version to 0.6.4.3

* [R] add an R package versioning section to the contributors guide

* [R] R-package/README.md: clean up the redundant old installation instructions, link the contributors guide
This commit is contained in:
Vadim Khotilovich
2017-05-02 00:51:34 -05:00
committed by Tong He
parent d769b6bcb5
commit a375ad2822
29 changed files with 351 additions and 246 deletions
Download Patch File Download Diff File Expand all files Collapse all files

16
R-package/R/xgb.plot.deepness.R
View File

@@ -63,7 +63,7 @@
xgb.plot.deepness <- function(model = NULL, which = c("2x1", "max.depth", "med.depth", "med.weight"),
plot = TRUE, ...) {
if (!(class(model) == "xgb.Booster" || is.data.table(model)))
if (!(inherits(model, "xgb.Booster") || is.data.table(model)))
stop("model: Has to be either an xgb.Booster model generaged by the xgb.train function\n",
"or a data.table result of the xgb.importance function")
@@ -73,14 +73,14 @@ xgb.plot.deepness <- function(model = NULL, which = c("2x1", "max.depth", "med.d
which <- match.arg(which)
dt_tree <- model
if (class(model) == "xgb.Booster")
if (inherits(model, "xgb.Booster"))
dt_tree <- xgb.model.dt.tree(model = model)
if (!all(c("Feature", "Tree", "ID", "Yes", "No", "Cover") %in% colnames(dt_tree)))
stop("Model tree columns are not as expected!\n",
" Note that this function works only for tree models.")
dt_depths <- merge(get.leaf.depth(dt_tree), dt_tree[, .(ID, Cover, Weight=Quality)], by = "ID")
dt_depths <- merge(get.leaf.depth(dt_tree), dt_tree[, .(ID, Cover, Weight = Quality)], by = "ID")
setkeyv(dt_depths, c("Tree", "ID"))
# count by depth levels, and also calculate average cover at a depth
dt_summaries <- dt_depths[, .(.N, Cover = mean(Cover)), Depth]
@@ -89,13 +89,13 @@ xgb.plot.deepness <- function(model = NULL, which = c("2x1", "max.depth", "med.d
if (plot) {
if (which == "2x1") {
op <- par(no.readonly = TRUE)
par(mfrow=c(2,1),
par(mfrow = c(2,1),
oma = c(3,1,3,1) + 0.1,
mar = c(1,4,1,0) + 0.1)
dt_summaries[, barplot(N, border=NA, ylab = 'Number of leafs', ...)]
dt_summaries[, barplot(N, border = NA, ylab = 'Number of leafs', ...)]
dt_summaries[, barplot(Cover, border=NA, ylab = "Weighted cover", names.arg=Depth, ...)]
dt_summaries[, barplot(Cover, border = NA, ylab = "Weighted cover", names.arg = Depth, ...)]
title("Model complexity", xlab = "Leaf depth", outer = TRUE, line = 1)
par(op)
@@ -119,8 +119,8 @@ xgb.plot.deepness <- function(model = NULL, which = c("2x1", "max.depth", "med.d
get.leaf.depth <- function(dt_tree) {
# extract tree graph's edges
dt_edges <- rbindlist(list(
dt_tree[Feature != "Leaf", .(ID, To=Yes, Tree)],
dt_tree[Feature != "Leaf", .(ID, To=No, Tree)]
dt_tree[Feature != "Leaf", .(ID, To = Yes, Tree)],
dt_tree[Feature != "Leaf", .(ID, To = No, Tree)]
))
# whether "To" is a leaf:
dt_edges <-