report

docs/report.tex

@@ -194,6 +194,8 @@ image no concatenation has to be done of course. The SVM can be trained with a
 subset of the given dataset called the ''Learning set''. Once trained, the
 entire classifier can be saved as a Pickle object\footnote{See
 \url{http://docs.python.org/library/pickle.html}} for later usage.
+In our case the support vector machine uses a radial gauss kernel. The SVM finds
+a seperating hyperplane with minimum margins.
 
 \section{Implementation}