modify disadvantage
[MRG+2] modify disadvantage
@@ -28,7 +28,8 @@ The advantages of support vector machines are:
The disadvantages of support vector machines include:
- If the number of features is much greater than the number of
- samples, the method is likely to give poor performances.
+ samples, avoid over-fitting in choosing :ref:`svm_kernels` and regularization
+ term is crucial.
- SVMs do not directly provide probability estimates, these are
calculated using an expensive five-fold cross-validation
