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Commit 365deb2d authored by Richard Torenvliet's avatar Richard Torenvliet
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added some changes to report

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......@@ -387,7 +387,7 @@ Performs a grid-search to find the optimal value for \texttt{c} and
\texttt{gamma}, for the given combination of NEIGHBOURS and BLUR\_SCALE. The
optimal classifier is saved in
\emph{data/classifier\_\{BLUR\_SCALE\}\_\{NEIGBOURS\}.dat}, and the accuracy
scores are saved in in
scores are saved in
\emph{results/results\_\{BLUR\_SCALE\}\_\{NEIGBOURS\}.txt}.
Like \texttt{create\_classifier.py}, the script ensures that the required
......@@ -675,7 +675,7 @@ function for each comparison, which is expensive in terms of efficiency. The
functions also call \texttt{inImage}, which (obviously) checks if a pixel is
inside the image. This can be avoided by adding a border around the image with
the width of half the neighbourhood size minus one (for example, $\frac{5 -
1}{2} = 2$ pixels in a $5x5$ neighbourhood). When creating the feature vector,
1}{2} = 2$ pixels in a 5x5 neighbourhood). When creating the feature vector,
this border should not be iterated over.
\section{Conclusion}
......
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