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adding bootstrap-emq

This commit is contained in:
Alejandro Moreo Fernandez 2025-12-08 12:17:54 +01:00
parent 7342e57cda
commit 7b75954f9b
1 changed files with 4 additions and 1 deletions
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5
BayesianKDEy/full_experiments.py
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@ -10,7 +10,7 @@ from copy import deepcopy as cp
import quapy as qp import quapy as qp
from BayesianKDEy._bayeisan_kdey import BayesianKDEy from BayesianKDEy._bayeisan_kdey import BayesianKDEy
from build.lib.quapy.data import LabelledCollection from build.lib.quapy.data import LabelledCollection
from quapy.method.aggregative import DistributionMatchingY as DMy, AggregativeQuantifier from quapy.method.aggregative import DistributionMatchingY as DMy, AggregativeQuantifier, EMQ
from quapy.method.base import BinaryQuantifier, BaseQuantifier from quapy.method.base import BinaryQuantifier, BaseQuantifier
from quapy.model_selection import GridSearchQ from quapy.model_selection import GridSearchQ
from quapy.data import Dataset from quapy.data import Dataset
@ -54,6 +54,7 @@ def methods():
quantifier with optimized hyperparameters quantifier with optimized hyperparameters
""" """
acc_hyper = {} acc_hyper = {}
emq_hyper = {'calib': [None, 'nbvs', 'bcts', 'ts', 'vs']}
hdy_hyper = {'nbins': [3,4,5,8,16,32]} hdy_hyper = {'nbins': [3,4,5,8,16,32]}
kdey_hyper = {'bandwidth': [0.001, 0.005, 0.01, 0.05, 0.1, 0.2]} kdey_hyper = {'bandwidth': [0.001, 0.005, 0.01, 0.05, 0.1, 0.2]}
kdey_hyper_clr = {'bandwidth': [0.05, 0.1, 0.5, 1., 2., 5.]} kdey_hyper_clr = {'bandwidth': [0.05, 0.1, 0.5, 1., 2., 5.]}
@ -65,6 +66,8 @@ def methods():
yield 'BootstrapACC', ACC(LR()), acc_hyper, lambda hyper: AggregativeBootstrap(ACC(LR()), n_test_samples=1000, random_state=0), multiclass_method yield 'BootstrapACC', ACC(LR()), acc_hyper, lambda hyper: AggregativeBootstrap(ACC(LR()), n_test_samples=1000, random_state=0), multiclass_method
yield 'BayesianACC', ACC(LR()), acc_hyper, lambda hyper: BayesianCC(LR(), mcmc_seed=0), multiclass_method yield 'BayesianACC', ACC(LR()), acc_hyper, lambda hyper: BayesianCC(LR(), mcmc_seed=0), multiclass_method
yield 'BootstrapEMQ', EMQ(LR(), on_calib_error='backup'), emq_hyper, lambda hyper: AggregativeBootstrap(EMQ(LR(), on_calib_error='backup'), n_test_samples=1000, random_state=0), multiclass_method
yield 'BootstrapHDy', DMy(LR()), hdy_hyper, lambda hyper: AggregativeBootstrap(DMy(LR(), **hyper), n_test_samples=1000, random_state=0), multiclass_method yield 'BootstrapHDy', DMy(LR()), hdy_hyper, lambda hyper: AggregativeBootstrap(DMy(LR(), **hyper), n_test_samples=1000, random_state=0), multiclass_method
yield 'BayesianHDy', DMy(LR()), hdy_hyper, lambda hyper: PQ(LR(), stan_seed=0, **hyper), only_binary yield 'BayesianHDy', DMy(LR()), hdy_hyper, lambda hyper: PQ(LR(), stan_seed=0, **hyper), only_binary