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authornunzip <np.scarh@gmail.com>2018-11-20 18:56:19 +0000
committernunzip <np.scarh@gmail.com>2018-11-20 18:56:19 +0000
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tree4352841edbc40578d8ea717cd3fe1f6a7c64aa2c
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parent83ad9d43910641e5eb37bd488afc6375c12a9f32 (diff)
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Merge branch 'master' of skozl.com:e4-pattern
-rwxr-xr-xreport/metadata.yaml4
-rwxr-xr-xreport/paper.md4
2 files changed, 5 insertions, 3 deletions
diff --git a/report/metadata.yaml b/report/metadata.yaml
index 97c0c24..5c4dde1 100755
--- a/report/metadata.yaml
+++ b/report/metadata.yaml
@@ -2,9 +2,7 @@
title: 'EE4-68 Pattern Recognition (2018-2019) CW1'
author:
- name: Vasil Zlatanov (01120518), Nunzio Pucci (01113180)
- affilation: Imperial College
- location: London, UK
- email: vz215@ic.ac.uk, np1915@ic.ac.uk
+ location: vz215@ic.ac.uk, np1915@ic.ac.uk
numbersections: yes
lang: en
babel-lang: english
diff --git a/report/paper.md b/report/paper.md
index aa998b4..5c145c2 100755
--- a/report/paper.md
+++ b/report/paper.md
@@ -461,6 +461,10 @@ Seed & Individual$(M=120)$ & Bag + Feature Ens.$(M=60+95)$\\ \hline
\label{tab:compare}
\end{table}
+# Conclusion
+
+We have looked at the relevance of PCA and LDA when applied to face recognition, and analyzed the individual and combined performance. We have further looked at improvements made available by ensemble learning, utilising data and feature randomisation together with PCA-LDA and found it to be an effective approach to face recognition.
+
# References
<div id="refs"></div>