From 0ee590d58095e13d2975f0a4159c22f78f485abe Mon Sep 17 00:00:00 2001
From: Michael I Chen <michael.chen.0@gmail.com>
Date: Tue, 12 Apr 2022 01:48:53 -0700
Subject: [PATCH] Correct a typo in documentation (#23116)

extend -> extent
---
 sklearn/decomposition/_kernel_pca.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/sklearn/decomposition/_kernel_pca.py b/sklearn/decomposition/_kernel_pca.py
index fba2fce3d4547..4e3ad720ae126 100644
--- a/sklearn/decomposition/_kernel_pca.py
+++ b/sklearn/decomposition/_kernel_pca.py
@@ -75,7 +75,7 @@ class KernelPCA(_ClassNamePrefixFeaturesOutMixin, TransformerMixin, BaseEstimato
             default='auto'
         Select eigensolver to use. If `n_components` is much
         less than the number of training samples, randomized (or arpack to a
-        smaller extend) may be more efficient than the dense eigensolver.
+        smaller extent) may be more efficient than the dense eigensolver.
         Randomized SVD is performed according to the method of Halko et al
         [3]_.