AI RESEARCH
Fractionally Supervised Classification with Maxima Nominated Samples
arXiv CS.LG
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ArXi:2604.25145v1 Announce Type: cross Fractionally supervised classification (FSC) offers a flexible framework for combining labeled and unlabeled data in model-based classification, but existing formulations assume simple random sampling. In many applications, however, the retained observation is an extreme order statistic from a set rather than a randomly selected unit.