nips nips2006 nips2006-155 nips2006-155-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Ran El-Yaniv, Mordechai Nisenson
Abstract: We consider single-class classification (SCC) as a two-person game between the learner and an adversary. In this game the target distribution is completely known to the learner and the learner’s goal is to construct a classifier capable of guaranteeing a given tolerance for the false-positive error while minimizing the false negative error. We identify both “hard” and “soft” optimal classification strategies for different types of games and demonstrate that soft classification can provide a significant advantage. Our optimal strategies and bounds provide worst-case lower bounds for standard, finite-sample SCC and also motivate new approaches to solving SCC.
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