Home | Trees | Indices | Help |
|
---|
|
Support Vector Machine Classifier. Base class for all external SVM implementations. Derived classes should define: * _KERNELS: map(dict) should define assignment to a tuple containing implementation kernel type, list of parameters adherent to the kernel, and sensitivity analyzer e.g.:: _KERNELS = { 'linear': (shogun.Kernel.LinearKernel, (), LinearSVMWeights), 'rbf' : (shogun.Kernel.GaussianKernel, ('gamma',), None), ... }
|
|||
Inherited from |
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
Inherited from Inherited from Inherited from Inherited from |
|
|||
_ATTRIBUTE_COLLECTIONS = ['params', 'kernel_params']
|
|||
_SVM_PARAMS = {'C': Parameter(-1.0, descr= 'Trade-off paramete
|
|||
_clf_internals = ['svm', 'kernel-based'] Describes some specifics about the classifier -- is that it is doing regression for instance.... |
|||
Inherited from Inherited from |
|
|||
Inherited from |
|
|||
Inherited from Inherited from |
|
Init base class of SVMs. Not to be publicly used TODO: handling of parameters might migrate to be generic for all classifiers. SVMs are choosen to be testbase for that functionality to see how well it would fit.
|
|
Compute default C TODO: for non-linear SVMs |
Compute default Gamma TODO: unify bloody libsvm interface so it makes use of this function. Now it is computed within SVMModel.__init__ |
|
|
_SVM_PARAMS
|
Home | Trees | Indices | Help |
|
---|
Generated by Epydoc 3.0.1 on Sun Jun 1 19:01:48 2008 | http://epydoc.sourceforge.net |