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.