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bayesianCC with custom prior

This commit is contained in:
Alejandro Moreo Fernandez 2026-01-13 13:08:07 +01:00
parent 47dc6acc75
commit ce51766944
1 changed files with 2 additions and 7 deletions
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9
BayesianKDEy/prior_effect.py
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@ -32,13 +32,8 @@ def methods():
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.]}
yield 'BayesianACC', ACC(LR()), acc_hyper, lambda hyper: BayesianCC(LR(), mcmc_seed=0)
# yield f'BaKDE-Ait', KDEyCLR(LR()), kdey_hyper_clr, lambda hyper: BayesianKDEy(kernel='aitchison',
mcmc_seed=0,
engine='numpyro',
temperature=None,
prior='uniform',
**hyper)
yield 'BayesianACC', ACC(LR()), acc_hyper, lambda hyper: BayesianCC(LR(), mcmc_seed=0, prior='uniform')
# yield f'BaKDE-Ait', KDEyCLR(LR()), kdey_hyper_clr, lambda hyper: BayesianKDEy(kernel='aitchison', mcmc_seed=0, engine='numpyro', temperature=None, prior='uniform', **hyper)
def run_test(test, alpha_test, alpha_train, concentration, prior_type, bay_quant, train_prev, results):