Constrained classification and ranking via quantiles
US11429894B2 Патенты
Example aspects of the present disclosure are directed to systems and methods for learning classification models which satisfy constraints such as , for example, constraints that can be expressed as a predicted positive rate or negative rate on a subset of the training dataset . In particular, through the use of quantile estimators , the systems and methods of the present disclosure can transform a constrained optimi zation problem into an unconstrained optimization problem that is solved more efficiently and generally than the con strained optimization problem . As one example, the uncon stra
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