physbo.search.score module

physbo.search.score.EI(predictor, training, test, fmax=None)

Maximum expected improvement.

パラメータ

• predictor (predictor object) -- Base class is defined in physbo.predictor.

• training (physbo.variable) -- Training dataset. If already trained, the model does not use this.

• test (physbo.variable) -- Inputs

• fmax (float) -- Max value of posterior probability distribution. If not set fmax, the max value of posterior mean of weights is set.

戻り値

score

戻り値の型

numpy.ndarray

physbo.search.score.PI(predictor, training, test, fmax=None)

Maximum probability of improvement.

パラメータ

• predictor (predictor object) -- Base class is defined in physbo.predictor.

• training (physbo.variable) -- Training dataset. If already trained, the model does not use this.

• test (physbo.variable) -- Inputs

• fmax (float) -- Max value of posterior probability distribution. If not set fmax, the max value of posterior mean of weights is set.

戻り値

score

戻り値の型

numpy.ndarray

physbo.search.score.TS(predictor, training, test, alpha=1)

Thompson sampling (See Sec. 2.1 in Materials Discovery Volume 4, June 2016, Pages 18-21)

パラメータ

• predictor (predictor object) -- Base class is defined in physbo.predictor.

• training (physbo.variable) -- Training dataset. If already trained, the model does not use this.

• test (physbo.variable) -- Inputs

• alpha (float) -- noise for sampling source (default: 1.0)

戻り値

score

戻り値の型

numpy.ndarray