diff --git a/Advance_Practice_and_Unsupervised_Learning/AP_Clustering_Algo.tex b/Advance_Practice_and_Unsupervised_Learning/AP_Clustering_Algo.tex
index 1c3a27f..b36b8e8 100644
--- a/Advance_Practice_and_Unsupervised_Learning/AP_Clustering_Algo.tex
+++ b/Advance_Practice_and_Unsupervised_Learning/AP_Clustering_Algo.tex
@@ -407,7 +407,7 @@ \section{Distance Measures}
 		      $$
 		\item \textbf{Minkowski distance}  is a generalized distance measure, with the power allowed to vary.
 		      $$
-			      d_{m}(j, k)=\left(\sum_{i=1}^{p}\left|x_{i j}-x_{i k}\right|^{1 / m}\right)^{1 / m}
+			     d_{m}(j, k)=\left(\sum_{i=1}^{p}\left|x_{i j}-x_{i k}\right|^m\right)^{1 / m}
 		      $$
 
 		      Euclidean distance is equivalent to Minkowski distance with \(m=2\), and Manhattan distance is equivalent to Minkowski