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| -rwxr-xr-x | report/paper.md | 6 |
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 |