From 4c8e9567ca10bc674329e89febdd2c157b546f40 Mon Sep 17 00:00:00 2001
From: Vidushi Gupta <55969597+Vidushi-Gupta@users.noreply.github.com>
Date: Thu, 8 Jun 2023 12:09:11 +0530
Subject: [PATCH] Fixed spacing

Added a space after the full-stop and capitalised the initial.
---
 5-Clustering/2-K-Means/README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/5-Clustering/2-K-Means/README.md b/5-Clustering/2-K-Means/README.md
index 628ecbb1..4ad4110a 100644
--- a/5-Clustering/2-K-Means/README.md
+++ b/5-Clustering/2-K-Means/README.md
@@ -134,7 +134,7 @@ You see an array printed out with predicted clusters (0, 1,or 2) for each row of
 
 ## Silhouette score
 
-Look for a silhouette score closer to 1. This score varies from -1 to 1, and if the score is 1, the cluster is dense and well-separated from other clusters. A value near 0 represents overlapping clusters with samples very close to the decision boundary of the neighboring clusters.[source](https://dzone.com/articles/kmeans-silhouette-score-explained-with-python-exam). 
+Look for a silhouette score closer to 1. This score varies from -1 to 1, and if the score is 1, the cluster is dense and well-separated from other clusters. A value near 0 represents overlapping clusters with samples very close to the decision boundary of the neighboring clusters. [(Source)](https://dzone.com/articles/kmeans-silhouette-score-explained-with-python-exam)
 
 Our score is **.53**, so right in the middle. This indicates that our data is not particularly well-suited to this type of clustering, but let's continue.