Double Logistic Regression Approach to Biased Positive-Unlabeled Data
Konrad Furmańczyk,
Jan Mielniczuk,
Wojciech Rejchel
et al.
Abstract:Positive and unlabelled learning is an important non-standard inference problem which arises naturally in many applications. The significant limitation of almost all existing methods addressing it lies in assuming that the propensity score function is constant and does not depend on features (Selected Completely at Random assumption), which is unrealistic in many practical situations. Avoiding this assumption, we consider parametric approach to the problem of joint estimation of posterior probability and prope… Show more
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