Outliers in rules - the comparision of LOF, COF and KMEANS algorithms
Authors:
- Agnieszka Justyna Nowak-Brzezińska,
- Czesław Zbigniew Horyń
Abstract
The aim of the article is the analysis of using LOF, COF and Kmeans algorithms for outlier detection in rule based knowledge bases. The subject of outlier mining is very important nowadays. Outliers in rules mean unusual rules which are rare in comparison to others and should be explored further by the domain expert. In the research the authors use the outlier detection methods to find a given (1%, 5%, 10%) number of outliers in rules. Then, they analyze which of seven various quality indices, that they used for all rules and after removing selected outliers, improve the quality of rule clusters. In the experimental stage the authors used six different knowledge bases. The results show that the optimal results were achieved for COF outlier detection algorithm as the one for which, among all analyzed quality indices, the cluster quality improved most frequently.
- Record ID
- USL4819ad1af8ea41129b2dfb3667d6f3a3
- Author
- Journal series
- Procedia Computer Science, ISSN 1877-0509, Irregular
- Issue year
- 2020
- Vol
- 176
- Pages
- 1420-1429
- Publication size in sheets
- 0.50
- Keywords in English
- outliers, LOF, COF, quality indices, clustering
- DOI
- DOI:10.1016/j.procs.2020.09.152 Opening in a new tab
- Handle.net URL
- hdl.handle.net/20.500.12128/16856 Opening in a new tab
- URL
- https://www.sciencedirect.com/science/article/pii/S1877050920320524 Opening in a new tab
- Language
- eng (en) English
- License
- File
-
- File: 1
- Outliers in rules - the comparision of LOF, COF and KMEANS algorithms, File Nowak-Brzezinska_Outliers_in_rules-the_comparision_of_LOF_COF_and_KMEANS.pdf / 422 KB
- Nowak-Brzezinska_Outliers_in_rules-the_comparision_of_LOF_COF_and_KMEANS.pdf
- publication date: 21-09-2022
- Outliers in rules - the comparision of LOF, COF and KMEANS algorithms, File Nowak-Brzezinska_Outliers_in_rules-the_comparision_of_LOF_COF_and_KMEANS.pdf / 422 KB
-
- Score (nominal)
- 70
- Score source
- BIBLIOGRAFIA DOROBKU PRACOWNIKÓW UŚ
- Publication indicators
- Citation count
- 18
- Uniform Resource Identifier
- https://opus.us.edu.pl/info/article/USL4819ad1af8ea41129b2dfb3667d6f3a3/
- URN
urn:uni-kat-prod:USL4819ad1af8ea41129b2dfb3667d6f3a3
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.