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authornunzip <np.scarh@gmail.com>2018-11-20 19:04:07 +0000
committernunzip <np.scarh@gmail.com>2018-11-20 19:04:07 +0000
commit4fd68e20c8aba969438c5ce395226bd8c66e2721 (patch)
treeb9359401a7787293bb9deae7ffe710a5ab03796f
parent1e0e0800a64c0adcf13021795fa064e86efd3f74 (diff)
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Chop 1
-rwxr-xr-xreport/paper.md15
1 files changed, 7 insertions, 8 deletions
diff --git a/report/paper.md b/report/paper.md
index 5c145c2..f1bca34 100755
--- a/report/paper.md
+++ b/report/paper.md
@@ -114,9 +114,8 @@ The analysed classification methods used for face recognition are Nearest Neighb
alternative method utilising reconstruction error.
Nearest Neighbor projects the test data onto the generated subspace and finds the closest
-training sample to the projected test image, assigning the same class as that of the nearest neighbor.
-
-Recognition accuracy of NN classification can be observed in figure \ref{fig:accuracy}.
+training sample to the projected test image, assigning the same class as that of the nearest neighbor. Recognition accuracy
+of NN classification can be observed in figure \ref{fig:accuracy}.
A confusion matrix showing success and failure cases for Nearest Neighbor classification when using PCA can be observed in figure \ref{fig:cm}:
@@ -184,7 +183,7 @@ memory associated with storing the different eigenvectors is deallocated, the to
\end{center}
\end{figure}
-A confusion matrix showing success and failure cases for alternative method classification
+A confusion matrix showing success and failure cases for alternative method
can be observed in figure \ref{fig:cm-alt}.
\begin{figure}
@@ -291,7 +290,7 @@ are displayed in table \ref{tab:time}.
\begin{figure}
\begin{center}
\includegraphics[width=17em]{fig/ldapca3dacc.pdf}
-\caption{PCA-LDA NN Recognition Accuracy varying hyper-parameters}
+\caption{PCA-LDA NN Recognition Accuracy varying Mpca,Mlda}
\label{fig:ldapca_acc}
\end{center}
\end{figure}
@@ -306,7 +305,7 @@ Testing with $M_{\textrm{lda}}=50$ and $M_{\textrm{pca}}=115$ gives 92.9% accura
\begin{figure}
\begin{center}
\includegraphics[width=17em]{fig/cmldapca.pdf}
-\caption{PCA-LDA NN Recognition Confusion Matrix Mlda=50, Mpca=115}
+\caption{PCA-LDA NN Recognition CM, Mlda=50, Mpca=115}
\label{fig:ldapca_cm}
\end{center}
\end{figure}
@@ -531,8 +530,8 @@ LDA-PCA & 0.11 & 0.19 & 0.13 \\ \hline
\begin{figure}
\begin{center}
-\includegraphics[width=15em]{fig/memnn.pdf}
-\includegraphics[width=15em]{fig/memalt.pdf}
+\includegraphics{fig/memnn.pdf}
+\includegraphics{fig/memalt.pdf}
\caption{Memory Usage for NN and alternative method}
\label{fig:mem}
\end{center}