diff --git a/0.24/_sources/auto_examples/svm/plot_svm_anova.rst.txt b/0.24/_sources/auto_examples/svm/plot_svm_anova.rst.txt
index 40a95c326a58e..7b1683320335b 100644
--- a/0.24/_sources/auto_examples/svm/plot_svm_anova.rst.txt
+++ b/0.24/_sources/auto_examples/svm/plot_svm_anova.rst.txt
@@ -62,7 +62,7 @@ that our model achieves best performance when we select around 10% of features.
 
     # #############################################################################
     # Create a feature-selection transform, a scaler and an instance of SVM that we
-    # combine together to have an full-blown estimator
+    # combine together to have a full-blown estimator
     clf = Pipeline([('anova', SelectPercentile(chi2)),
                     ('scaler', StandardScaler()),
                     ('svc', SVC(gamma="auto"))])