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Negative selection algorithm (NSA) is an important method for generating detectors in artificial immune systems. Traditional NSAs randomly generate detectors in the whole feature space. However, with increasing dimensions, data samples aggregate in some specific subspaces, not uniformly distributed in the whole space. The detectors randomly generated by traditional NSAs cannot exactly fall into these...
Self/Non-self discrimination is the basic mission of the artificial immune systems (AIS). In traditional AIS, detectors discriminate non-self elements based on the Minkowski distance between detectors and antigens. However, in high dimensional feature space the distances between elements converge to a similar value, so the data discrimination will become much difficult. In this article, the relationship...
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