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adding experiment with ILR

This commit is contained in:
Alejandro Moreo Fernandez 2025-12-04 20:03:30 +01:00
parent e8d175106f
commit a6974b7624
1 changed files with 1 additions and 1 deletions
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BayesianKDEy/_bayeisan_kdey.py
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@ -166,7 +166,7 @@ class BayesianKDEy(AggregativeSoftQuantifier, KDEBase, WithConfidenceABC):
recent_accept_rate = np.mean(acceptance_history[-100:]) recent_accept_rate = np.mean(acceptance_history[-100:])
step_size *= np.exp(adapt_rate * (recent_accept_rate - target_acceptance)) step_size *= np.exp(adapt_rate * (recent_accept_rate - target_acceptance))
# step_size = float(np.clip(step_size, min_step, max_step)) # step_size = float(np.clip(step_size, min_step, max_step))
print(f'acceptance-rate={recent_accept_rate*100:.3f}%, step-size={step_size:.5f}') # print(f'acceptance-rate={recent_accept_rate*100:.3f}%, step-size={step_size:.5f}')
# remove "warmup" initial iterations # remove "warmup" initial iterations
samples = np.asarray(samples[self.num_warmup:]) samples = np.asarray(samples[self.num_warmup:])