Added comment to the class

Author: mridula-s109

docs/reference/elasticsearch/rest-apis/retrievers.md

@@ -287,10 +287,6 @@ Each entry specifies the following parameters:
 
     * `l2_norm` : An `L2ScoreNormalizer` that normalizes scores using the L2 norm of the score values.
 
-        ```
-        score = score / sqrt(sum(score_i^2))
-        ```
-
 See also [this hybrid search example](docs-content://solutions/search/retrievers-examples.md#retrievers-examples-linear-retriever) using a linear retriever on how to independently configure and apply normalizers to retrievers.
 
 `rank_window_size`

x-pack/plugin/rank-rrf/src/main/java/org/elasticsearch/xpack/rank/linear/L2ScoreNormalizer.java

@@ -10,6 +10,13 @@
 
 import org.apache.lucene.search.ScoreDoc;
 
+/**
+ * A score normalizer that applies L2 normalization to a set of scores.
+ * <p>
+ * This normalizer scales the scores so that the L2 norm of the score vector is 1,
+ * if possible. If all scores are zero or NaN, normalization is skipped and the original scores are returned.
+ * </p>
+ */
 public class L2ScoreNormalizer extends ScoreNormalizer {
 
     public static final L2ScoreNormalizer INSTANCE = new L2ScoreNormalizer();