pimkl.factories package

Submodules

pimkl.factories.estimator_factory module

estimator_factory.ESTIMATOR_FACTORY = {'EasyMKL': pymimkl.EasyMKL, 'SVC': <class 'sklearn.svm._classes.SVC'>}

pimkl.factories.induction_factory module

induction_factory.INDUCTION_FACTORY = {'induce_gaussian_kernel': pymimkl.induce_gaussian_kernel, 'induce_linear_kernel': pymimkl.induce_linear_kernel, 'induce_polynomial_kernel': pymimkl.induce_polynomial_kernel, 'induce_sigmoidal_kernel': pymimkl.induce_sigmoidal_kernel}

pimkl.factories.mkl_factory module

class pimkl.factories.mkl_factory.WeightedAverageMKL(*args: Any, **kwargs: Any)

Bases: AverageMKL

small wrapping of AverageMKL where the additional cunstructor parameter kernels_weights is used to predict a final kernel rather than the average.

The applied weights are corrected to sum up to one.

fit(X, y=None)

class pimkl.factories.mkl_factory.WeightedAverageMKL(*args: Any, **kwargs: Any)

Bases: AverageMKL

small wrapping of AverageMKL where the additional cunstructor parameter kernels_weights is used to predict a final kernel rather than the average.

The applied weights are corrected to sum up to one.

fit(X, y=None)

mkl_factory.MKL_FACTORY = {'AverageMKL': pymimkl.AverageMKL, 'EasyMKL': pymimkl.EasyMKL, 'UMKLKNN': pymimkl.UMKLKNN, 'WeightedAverageMKL': <class 'pimkl.factories.mkl_factory.WeightedAverageMKL'>}

Module contents