Update collections/_posts/2024-10-20-tabular-explainability.md

Co-authored-by: Nathan Painchaud <23144457+nathanpainchaud@users.noreply.github.com>

collections/_posts/2024-10-20-tabular-explainability.md

@@ -154,7 +154,7 @@ prediction was defined as that which corresponds to the highest attention value
 <p style="text-align: center;font-style:italic">Figure 5 - CT’s best group of features per method by class</p>
 
 * Analysis of the proportion of samples who considered each concept group to be the best for CT and segmented by predicted class
-* AVG demonstrates minimal to no alteration in its distribution according to the class, which sounds strange
+* AVG demonstrates minimal to no alteration in its distribution according to the class, which seems strange
 * MLA assigns explainability to three different concept groups for each class, with varying proportion depending on the class
 * Strong alignment between LL and MLA behaviors
 * Soil type seems to be a discriminating factor only for the LL and MLA methods