Abstract
In the paper, we introduce a novel method of estimating label frequency and parameters of the logistic model for positive and unlabeled (PU) data. Our approach is based on Gibbs sampler that uses Pólya-Gamma latent variables for Bayesian logistic model. In the paper, we focus on estimating label frequency, but the proposed method also provides estimated probabilities of being positive observation among the unlabeled ones.
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