73 lines
1.3 KiB
Python
73 lines
1.3 KiB
Python
import warnings
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from sklearn.exceptions import ConvergenceWarning
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warnings.simplefilter("ignore", ConvergenceWarning)
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from . import confidence
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from . import base
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from . import aggregative
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from . import non_aggregative
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from . import meta
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AGGREGATIVE_METHODS = {
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aggregative.CC,
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aggregative.ACC,
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aggregative.PCC,
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aggregative.PACC,
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aggregative.EMQ,
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aggregative.HDy,
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aggregative.DyS,
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aggregative.SMM,
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aggregative.X,
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aggregative.T50,
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aggregative.MAX,
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aggregative.MS,
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aggregative.MS2,
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aggregative.DMy,
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aggregative.KDEyML,
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aggregative.KDEyCS,
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aggregative.KDEyHD,
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# aggregative.OneVsAllAggregative,
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confidence.BayesianCC,
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}
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BINARY_METHODS = {
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aggregative.HDy,
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aggregative.DyS,
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aggregative.SMM,
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aggregative.X,
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aggregative.T50,
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aggregative.MAX,
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aggregative.MS,
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aggregative.MS2,
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}
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MULTICLASS_METHODS = {
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aggregative.CC,
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aggregative.ACC,
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aggregative.PCC,
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aggregative.PACC,
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aggregative.EMQ,
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aggregative.KDEyML,
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aggregative.KDEyCS,
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aggregative.KDEyHD,
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confidence.BayesianCC
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}
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NON_AGGREGATIVE_METHODS = {
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non_aggregative.MaximumLikelihoodPrevalenceEstimation,
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non_aggregative.DMx
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}
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META_METHODS = {
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meta.Ensemble,
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meta.QuaNet
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}
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QUANTIFICATION_METHODS = AGGREGATIVE_METHODS | NON_AGGREGATIVE_METHODS | META_METHODS
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