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Preference Learning
Preference Learning
Class or Function Names PLMBOSampler Installation pip install -r https://hub.optuna.org/samplers/plmbo/requirements.txt Example from __future__ import annotations import matplotlib.pyplot as plt import optuna import optunahub from optuna.distributions import FloatDistribution import numpy as np PLMBOSampler = optunahub.load_module( # type: ignore "samplers/plmbo", ).PLMBOSampler if __name__ == "__main__": f_sigma = 0.01 def obj_func1(x): return np.sin(x[0]) + x[1] def obj_func2(x): return -np.sin(x[0]) - x[1] + 0.1 def obs_obj_func(x): return np.array( [ obj_func1(x) + np.random.normal(0, f_sigma), obj_func2(x) + np.