# Active Learning for cl-libsvm

*Tags*: `ai`

, `lisp`

, *Date*: 2009-06-22

Along the lines of active learning with python &
libsvm,
I added support for
calculating distance of a point from the separating hyperplane to
cl-libsvm. In binary classification,
there is only one SVM involved and one hyperplane. However, with
N-class problems, there is a binary SVM for each of the $N(N-1)/2$
pairs of classes, and there are as many separating hyperplanes,
something the linked python code fails to take into account. As per
the libsvm
FAQ, the
absolute value of the decision value (see `PREDICT-VALUES`

, wrapper
of `svm_predict_values`

) divided by the norm of the normal vector of
the separating hyperplane is the distance. `PREDICT-VALUES`

and
`MODEL-W2S`

are sufficient to calculate it. Note that among the
distributed binaries only the linux-x86 version has been recompiled
with the necessary changes, but patched sources are also included
for your recompiling pleasure.