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The Cartographer
Anomaly Detection with the Voronoi Diagram Evolutionary Algorithm
October 27, 2016 Β· Declared Dead Β· π Parallel Problem Solving from Nature
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Authors
Marti Luis, Fansi-Tchango Arsene, Navarro Laurent, Marc Schoenauer
arXiv ID
1610.08640
Category
cs.AI: Artificial Intelligence
Citations
6
Venue
Parallel Problem Solving from Nature
Last Checked
4 months ago
Abstract
This paper presents the Voronoi diagram-based evolutionary algorithm (VorEAl). VorEAl partitions input space in abnormal/normal subsets using Voronoi diagrams. Diagrams are evolved using a multi-objective bio-inspired approach in order to conjointly optimize classification metrics while also being able to represent areas of the data space that are not present in the training dataset. As part of the paper VorEAl is experimentally validated and contrasted with similar approaches.
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