From 858169eab2043dbacfe160f7e6873501c13f8287 Mon Sep 17 00:00:00 2001
From: nunzip <np.scarh@gmail.com>
Date: Tue, 20 Nov 2018 18:10:00 +0000
Subject: Add variance part 1

---
 report/paper.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/report/paper.md b/report/paper.md
index bd7ef71..32db134 100755
--- a/report/paper.md
+++ b/report/paper.md
@@ -42,8 +42,8 @@ figure \ref{fig:mean_face}.
 \end{center}
 \end{figure}
 
-To perform face recognition best M eigenvectors associated with the 
-largest eigenvalues are chosen. We found that the opimal value for M
+To perform face recognition the best M eigenvectors associated with the 
+largest eigenvalues (carrying the largest data variance, fig. \ref{fig:eigvariance}) are chosen. We found that the opimal value for M
 when when performing PCA is $M=99$ with an accuracy of 57%. For larger M
 the accuracy plateaus.
 
-- 
cgit v1.2.3-54-g00ecf