From 83191f0839ad4b729b61fee0e12e7349ade84a62 Mon Sep 17 00:00:00 2001
From: Thomas Lynn <32374143+lynntf@users.noreply.github.com>
Date: Sat, 14 Oct 2023 10:38:58 +0200
Subject: [PATCH] Update learning_to_rank.rst; Correct qid sort in snippet
 (#9673)

---
 doc/tutorials/learning_to_rank.rst | 1 +
 1 file changed, 1 insertion(+)

diff --git a/doc/tutorials/learning_to_rank.rst b/doc/tutorials/learning_to_rank.rst
index c562dc2df..015f736e0 100644
--- a/doc/tutorials/learning_to_rank.rst
+++ b/doc/tutorials/learning_to_rank.rst
@@ -58,6 +58,7 @@ Notice that the samples are sorted based on their query index in a non-decreasin
   sorted_idx = np.argsort(qid)
   X = X[sorted_idx, :]
   y = y[sorted_idx]
+  qid = qid[sorted_idx]
 
 The simplest way to train a ranking model is by using the scikit-learn estimator interface. Continuing the previous snippet, we can train a simple ranking model without tuning: