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ilr only on multiclass

This commit is contained in:
Alejandro Moreo Fernandez 2025-12-04 20:10:25 +01:00
parent a6974b7624
commit 59ef17c86c
2 changed files with 10 additions and 6 deletions
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2
BayesianKDEy/_bayeisan_kdey.py
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@ -128,7 +128,7 @@ class BayesianKDEy(AggregativeSoftQuantifier, KDEBase, WithConfidenceABC):
elif self.explore=='ilr': elif self.explore=='ilr':
ilr = ILRtransformation() ilr = ILRtransformation()
ilr_point = ilr(prev) ilr_point = ilr(prev)
dir_noise = rng.normal(scale=step_size, size=d) dir_noise = rng.normal(scale=step_size, size=d-1)
ilr_neighbour = ilr_point + dir_noise ilr_neighbour = ilr_point + dir_noise
neighbour = ilr.inverse(ilr_neighbour) neighbour = ilr.inverse(ilr_neighbour)
assert in_simplex(neighbour), 'wrong ILR transformation' assert in_simplex(neighbour), 'wrong ILR transformation'

14
BayesianKDEy/full_experiments.py
View File

@ -49,8 +49,10 @@ def methods():
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.]}
only_binary = True
multiclass_method = False multiclass_method = 'multiclass'
only_binary = 'only_binary'
only_multiclass = 'only_multiclass'
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
@ -63,7 +65,7 @@ def methods():
yield 'BayesianKDEy*', KDEyCLR(LR()), kdey_hyper_clr, lambda hyper: BayesianKDEy(kernel='aitchison', mcmc_seed=0, **hyper), multiclass_method yield 'BayesianKDEy*', KDEyCLR(LR()), kdey_hyper_clr, lambda hyper: BayesianKDEy(kernel='aitchison', mcmc_seed=0, **hyper), multiclass_method
yield 'BayKDEy*CLR', KDEyCLR(LR()), kdey_hyper_clr, lambda hyper: BayesianKDEy(kernel='aitchison', mcmc_seed=0, explore='clr', step_size=.15, **hyper), multiclass_method yield 'BayKDEy*CLR', KDEyCLR(LR()), kdey_hyper_clr, lambda hyper: BayesianKDEy(kernel='aitchison', mcmc_seed=0, explore='clr', step_size=.15, **hyper), multiclass_method
# yield 'BayKDEy*CLR2', KDEyCLR(LR()), kdey_hyper_clr, lambda hyper: BayesianKDEy(kernel='aitchison', mcmc_seed=0, explore='clr', step_size=.05, **hyper), multiclass_method # yield 'BayKDEy*CLR2', KDEyCLR(LR()), kdey_hyper_clr, lambda hyper: BayesianKDEy(kernel='aitchison', mcmc_seed=0, explore='clr', step_size=.05, **hyper), multiclass_method
yield 'BayKDEy*ILR', KDEyCLR(LR()), kdey_hyper_clr, lambda hyper: BayesianKDEy(kernel='aitchison', mcmc_seed=0, explore='ilr', step_size=.15, **hyper), multiclass_method yield 'BayKDEy*ILR', KDEyCLR(LR()), kdey_hyper_clr, lambda hyper: BayesianKDEy(kernel='aitchison', mcmc_seed=0, explore='ilr', step_size=.15, **hyper), only_multiclass
def model_selection(train: LabelledCollection, point_quantifier: AggregativeQuantifier, grid: dict): def model_selection(train: LabelledCollection, point_quantifier: AggregativeQuantifier, grid: dict):
@ -161,8 +163,10 @@ if __name__ == '__main__':
is_binary = data.n_classes==2 is_binary = data.n_classes==2
result_subdir = result_dir / ('binary' if is_binary else 'multiclass') result_subdir = result_dir / ('binary' if is_binary else 'multiclass')
hyper_subdir = result_dir / 'hyperparams' / ('binary' if is_binary else 'multiclass') hyper_subdir = result_dir / 'hyperparams' / ('binary' if is_binary else 'multiclass')
for method_name, method, hyper_params, withconf_constructor, only_binary in methods(): for method_name, method, hyper_params, withconf_constructor, method_scope in methods():
if only_binary and not is_binary: if method_scope == 'only_binary' and not is_binary:
continue
if method_scope == 'only_multiclass' and is_binary:
continue continue
result_path = experiment_path(result_subdir, data_name, method_name) result_path = experiment_path(result_subdir, data_name, method_name)
hyper_path = experiment_path(hyper_subdir, data_name, method.__class__.__name__) hyper_path = experiment_path(hyper_subdir, data_name, method.__class__.__name__)