Add support for SVDD (one-class SVM) #2807 #3013
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I don't understand how this can be used from scikit-learn? It seems to me like this feature isn't finished. Can you do an example that compares SVDD to standard one class SVM, please. |
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Support Vector Data Description (SVDD) could be a nice enhancement to OneClassSVM implementation.
A technical implementation is described in this paper:
http://www.csie.ntu.edu.tw/~cjlin/papers/svdd.pdf
Source code compatible with libsvm is available here:
http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/#libsvm_for_svdd_and_finding_the_smallest_sphere_containing_all_data
I have modified the sklearn/svm/src/libsvm/svm.h and svm.cpp files to add additional functionality of SVM.
-s 5 SVDD
-s 6 R^2 L1SVM
-s 7 R^2 L2SVM