Fixed typo.

docs/report.tex

@@ -624,7 +624,7 @@ if we can use every character in the dataset to train the SVM.
 
 It could be useful to check the number of support vectors used by the SVM. If
 this number is high in proportion to the number of dimensions in the feature
-vectors, it may be profitable to use a more simple type of SVM.
+vectors, it may be profitable to use a more simple kernel type for the SVM.
 
 \subsection{Other Local Binary Patterns}