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| author | Vasil Zlatanov <v@skozl.com> | 2018-11-20 18:40:43 +0000 |
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| committer | Vasil Zlatanov <v@skozl.com> | 2018-11-20 18:40:43 +0000 |
| commit | 646a0e43c4a52d16528c9d2692143e90b56e8774 (patch) | |
| tree | fe0d518a4c7dd40e58ee06e6b6329700e1671fcb | |
| parent | e4c77bbbd26637bd75712686ccec90b1fc95ad56 (diff) | |
| download | vz215_np1915-646a0e43c4a52d16528c9d2692143e90b56e8774.tar.gz vz215_np1915-646a0e43c4a52d16528c9d2692143e90b56e8774.tar.bz2 vz215_np1915-646a0e43c4a52d16528c9d2692143e90b56e8774.zip | |
Add conclusion
| -rwxr-xr-x | report/paper.md | 4 |
1 files changed, 4 insertions, 0 deletions
diff --git a/report/paper.md b/report/paper.md index 0f385c1..af24be3 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 improvement made available by ensemble learning, utilising data and feature randomisation together with PCA-LDA and found that it is an effective approach to face recognition. + # References <div id="refs"></div> |