The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model
Outlier detection in linear data sets has been done vigorously but only a small amount of work has been done for outlier detection in circular data. In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. Clustering technique basically...
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| Format: | Article |
| Language: | English |
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AIP Publishing
2017
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| Online Access: | http://umpir.ump.edu.my/id/eprint/30297/ http://umpir.ump.edu.my/id/eprint/30297/1/2017%20Di%20et%20al%20AIP%201842.pdf |
| _version_ | 1848823477011742720 |
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| author | Nur Faraidah, Muhammad Di Siti Zanariah, Satari |
| author_facet | Nur Faraidah, Muhammad Di Siti Zanariah, Satari |
| author_sort | Nur Faraidah, Muhammad Di |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Outlier detection in linear data sets has been done vigorously but only a small amount of work has been done for outlier detection in circular data. In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. Clustering technique basically utilizes distance measure to define distance between various data points. Here, we introduce the similarity distance based on Euclidean distance for circular model and obtain a cluster tree using the single linkage clustering algorithm. Then, a stopping rule for the cluster tree based on the mean direction and circular standard deviation of the tree height is proposed. We classify the cluster group that exceeds the stopping rule as potential outlier. Our aim is to demonstrate the effectiveness of proposed algorithms with the similarity distances in detecting the outliers. It is found that the proposed methods are performed well and applicable for circular regression model. |
| first_indexed | 2025-11-15T02:57:45Z |
| format | Article |
| id | ump-30297 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:57:45Z |
| publishDate | 2017 |
| publisher | AIP Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-302972021-09-27T00:46:03Z http://umpir.ump.edu.my/id/eprint/30297/ The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model Nur Faraidah, Muhammad Di Siti Zanariah, Satari QA Mathematics Outlier detection in linear data sets has been done vigorously but only a small amount of work has been done for outlier detection in circular data. In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. Clustering technique basically utilizes distance measure to define distance between various data points. Here, we introduce the similarity distance based on Euclidean distance for circular model and obtain a cluster tree using the single linkage clustering algorithm. Then, a stopping rule for the cluster tree based on the mean direction and circular standard deviation of the tree height is proposed. We classify the cluster group that exceeds the stopping rule as potential outlier. Our aim is to demonstrate the effectiveness of proposed algorithms with the similarity distances in detecting the outliers. It is found that the proposed methods are performed well and applicable for circular regression model. AIP Publishing 2017 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/30297/1/2017%20Di%20et%20al%20AIP%201842.pdf Nur Faraidah, Muhammad Di and Siti Zanariah, Satari (2017) The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model. AIP Conference Proceedings, 1842 (030016). pp. 1-12. ISSN 978-0-7354-1512-6. (Published) http://dx.doi.org/10.1063/1.4982854 http://dx.doi.org/10.1063/1.4982854 |
| spellingShingle | QA Mathematics Nur Faraidah, Muhammad Di Siti Zanariah, Satari The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model |
| title | The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model |
| title_full | The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model |
| title_fullStr | The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model |
| title_full_unstemmed | The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model |
| title_short | The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model |
| title_sort | effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model |
| topic | QA Mathematics |
| url | http://umpir.ump.edu.my/id/eprint/30297/ http://umpir.ump.edu.my/id/eprint/30297/ http://umpir.ump.edu.my/id/eprint/30297/ http://umpir.ump.edu.my/id/eprint/30297/1/2017%20Di%20et%20al%20AIP%201842.pdf |