From 6028b7d2e348d057eae100f9822d513f8cce6eb5 Mon Sep 17 00:00:00 2001
From: david-cortes <david.cortes.rivera@gmail.com>
Date: Sat, 24 Aug 2024 20:41:12 +0200
Subject: [PATCH] add training metrics monitoring

---
 R-package/R/xgboost.R    | 10 +++++++++-
 R-package/man/xgboost.Rd |  4 ++++
 2 files changed, 13 insertions(+), 1 deletion(-)

diff --git a/R-package/R/xgboost.R b/R-package/R/xgboost.R
index 20a252b9dfd5..bbf9e11178d5 100644
--- a/R-package/R/xgboost.R
+++ b/R-package/R/xgboost.R
@@ -809,6 +809,8 @@ process.x.and.col.args <- function(
 #' rows in `x`.
 #' @param verbosity Verbosity of printing messages. Valid values of 0 (silent), 1 (warning),
 #' 2 (info), and 3 (debug).
+#' @param monitor_training Whether to monitor objective optimization progress on the input data.
+#' Note that same 'x' and 'y' data are used for both model fitting and evaluation.
 #' @param nthreads Number of parallel threads to use. If passing zero, will use all CPU threads.
 #' @param seed Seed to use for random number generation. If passing `NULL`, will draw a random
 #' number using R's PRNG system to use as seed.
@@ -895,6 +897,7 @@ xgboost <- function(
   nrounds = 100L,
   weights = NULL,
   verbosity = 0L,
+  monitor_training = verbosity > 0,
   nthreads = parallel::detectCores(),
   seed = 0L,
   monotone_constraints = NULL,
@@ -932,11 +935,16 @@ xgboost <- function(
 
   fn_dm <- if (use_qdm) xgb.QuantileDMatrix else xgb.DMatrix
   dm <- do.call(fn_dm, lst_args$dmatrix_args)
+  evals <- list()
+  if (monitor_training) {
+    evals <- list(train = dm)
+  }
   model <- xgb.train(
     params = params,
     data = dm,
     nrounds = nrounds,
-    verbose = verbosity
+    verbose = verbosity,
+    evals = evals
   )
   attributes(model)$metadata <- lst_args$metadata
   attributes(model)$call <- match.call()
diff --git a/R-package/man/xgboost.Rd b/R-package/man/xgboost.Rd
index 4af8f25ecc04..a0fed3d95beb 100644
--- a/R-package/man/xgboost.Rd
+++ b/R-package/man/xgboost.Rd
@@ -11,6 +11,7 @@ xgboost(
   nrounds = 100L,
   weights = NULL,
   verbosity = 0L,
+  monitor_training = verbosity > 0,
   nthreads = parallel::detectCores(),
   seed = 0L,
   monotone_constraints = NULL,
@@ -96,6 +97,9 @@ rows in `x`.}
 \item{verbosity}{Verbosity of printing messages. Valid values of 0 (silent), 1 (warning),
 2 (info), and 3 (debug).}
 
+\item{monitor_training}{Whether to monitor objective optimization progress on the input data.
+Note that same 'x' and 'y' data are used for both model fitting and evaluation.}
+
 \item{nthreads}{Number of parallel threads to use. If passing zero, will use all CPU threads.}
 
 \item{seed}{Seed to use for random number generation. If passing `NULL`, will draw a random