Applying Genetic Algorithms to Outlier Detection
Proceedings of the 6th International Conference on Genetic Algorithms
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Mining distance-based outliers in near linear time with randomization and a simple pruning rule
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
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A novel density-based distance measure and an outlier detection method using evolutionary search are presented in this paper. A fitness function based on nearest neighbor distances is proposed and the genetic recombination operators are designed to achieve a balance of exploration and exploitation in the nearest neighborhood space. The methodology is tested on datasets of varying sizes (small to moderate) and dimensionalities and performance is compared to existing evolutionary methods for outlier detection.