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PU classification under Non-SCAR: clustering-assisted logistic model with oversampling enhancement
This study addresses the PU classification problem under violations of the SCAR assumption. We investigate logistic regression-based approaches, namely the cluster method and its extensions with strict and non-strict Lasso regularization. The primary contribution of this work is the integration of t
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