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- W2007838160 abstract "Negative selection algorithms are immune-inspired classifiers that are trained on negative examples only. Classification is performed by generating detectors that match none of the negative examples, and these detectors are then matched against the elements to be classified. This can be a performance bottleneck: A large number of detectors may be required for acceptable sensitivity, or finding detectors that match none of the negative examples may be difficult. In this paper, we show how negative selection can be implemented without generating detectors explicitly, which for many detector types leads to polynomial time algorithms whereas the common approach to sample detectors randomly takes exponential time in the worst case." @default.
- W2007838160 created "2016-06-24" @default.
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- W2007838160 date "2010-07-07" @default.
- W2007838160 modified "2023-10-18" @default.
- W2007838160 title "Negative selection algorithms without generating detectors" @default.
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- W2007838160 doi "https://doi.org/10.1145/1830483.1830673" @default.
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