Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
An Evolutionary Algorithm to Generate Ellipsoid Detectors for Negative Selection

An Evolutionary Algorithm to Generate Ellipsoid Detectors for Negative Selection

Shapiro, Joseph M.

Paperback

General Education

ISBN10: 1288395884
ISBN13: 9781288395880
Publisher: Biblioscholar
Published: Dec 4 2012
Pages: 162
Weight: 0.66
Height: 0.35 Width: 7.44 Depth: 9.69
Language: English
Negative selection is a process from the biological immune system that can be applied to two-class (self and nonself) classification problems. Negative selection uses only one class (self) for training, which results in detectors for the other class (nonself). This paradigm is especially useful for problems in which only one class is available for training, such as network intrusion detection. Previous work has investigated hyper-rectangles and hyper-spheres as geometric detectors. This work proposes ellipsoids as geometric detectors. First, we establish a mathematical model for ellipsoids. We develop an algorithm to generate ellipsoids by training on only one class of data. Ellipsoid mutation operators, an objective function, and a convergence technique are described for the evolutionary algorithm that generates ellipsoid detectors.

Also in

General Education

View All