An Efficient Method for Outlying Aspect Mining Based on Genetic Algorithm
- 24 November 2022
- book chapter
- conference paper
- Published by Springer Science and Business Media LLC
Abstract
No abstract availableKeywords
This publication has 17 references indexed in Scilit:
- A new simple and efficient density estimator that enables fast systematic searchPattern Recognition Letters, 2018
- A novel approach for graph-based global outlier detection in social networksInternational Journal of Security and Networks, 2018
- Discovering outlying aspects in large datasetsData Mining and Knowledge Discovery, 2016
- Mining outlying aspects on numeric dataData Mining and Knowledge Discovery, 2015
- Explaining Outliers by Subspace SeparabilityPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2013
- HiCS: High Contrast Subspaces for Density-Based Outlier RankingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2012
- Kernel density estimation via diffusionThe Annals of Statistics, 2010
- A Novel Method for Detecting Outlying Subspaces in High-dimensional Databases Using Genetic AlgorithmIEEE International Conference on Data Mining (ICDM), 2006
- Example-Based Outlier Detection for High Dimensional DatasetsIPSJ Digital Courier, 2005
- HOS-MinerA System for Detecting Outlying Subspaces of High-dimensional DataPublished by Elsevier BV ,2004