2014年
Outlier Detection Based on Leave-One-Out Density Using Binary Decision Diagrams.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
- ,
- 巻
- 8444
- 号
- 2
- 開始ページ
- 486
- 終了ページ
- 497
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1007/978-3-319-06605-9_40
- 出版者・発行元
- Springer Verlag
We propose a novel method for detecting outliers based on the leave-one-out density. The leave-one-out density of a datum is defined as a ratio of the number of data inside a region to the volume of the region after the datum is removed from an original data set. We propose an efficient algorithm that evaluates the leave-one-out density of each datum on a set of regions around the datum by using binary decision diagrams. The time complexity of the proposed method is near linear with respect to the size of a data set, while the outlier detection accuracy is still comparable to other methods. Experimental results show the usefulness of the proposed method. © 2014 Springer International Publishing.
- リンク情報
- ID情報
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- DOI : 10.1007/978-3-319-06605-9_40
- ISSN : 1611-3349
- ISSN : 0302-9743
- DBLP ID : conf/pakdd/KutsunaY14
- SCOPUS ID : 84901271800