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authorVasil Zlatanov <v@skozl.com>2018-11-19 10:29:51 +0000
committerVasil Zlatanov <v@skozl.com>2018-11-19 10:29:51 +0000
commit9f1de68f0a058689c5f2a1f09012f57099326796 (patch)
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parent712ecc83c2b8c789b74c26f42885d6560b99328a (diff)
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Change table reference to tab
-rwxr-xr-xreport/paper.md6
1 files changed, 4 insertions, 2 deletions
diff --git a/report/paper.md b/report/paper.md
index b2d9fbd..d887919 100755
--- a/report/paper.md
+++ b/report/paper.md
@@ -73,7 +73,7 @@ and eigenvectors of the matrices A\textsuperscript{T}A (NxN) and AA\textsuperscr
(DxD)).
The first ten biggest eigenvalues obtained with each method
-are shown in table \ref{fig:table_eigen}.
+are shown in table \ref{tab:eigen}.
\begin{table}[ht]
\centering
@@ -91,7 +91,7 @@ PCA &Fast PCA\\
2.4396E+04 &2.4339E+04\\
\end{tabular}
\caption{Comparison of eigenvalues obtain with the two computation methods}
-\label{fig:table_eigen}
+\label{tab:eigen}
\end{table}
It can be proven that the eigenvalues obtained are mathematically the same,
@@ -387,5 +387,7 @@ the 3 features of the subspaces obtained are graphed.
# Question 3, LDA Ensemble for Face Recognition, PCA-LDA Ensemble
+
+
# References