Cover Image

Fuzzy Distance Measure Based Affinity Propagation Clustering

Affinity Propagation (AP) is an effective algorithm that find exemplars repeatedly exchange real valued messages between pairs of data points. AP uses the similarity between data points to calculate the messages. Hence, the construction of similarity is essential in the AP algorithm. A common choice...

Full description

Saved in:
Bibliographic Details
Main Authors: Al-Akash, Omar Mahmoud Nayef, Syed Ahmad, Sharifah Sakinah, Azmi, Mohd Sanusi
Format: Article
Language:English
Published: Research India Publications 2018
Subjects:
Q Science (General)
QA76 Computer software
Online Access:http://eprints.utem.edu.my/id/eprint/22848/2/non-indeks%20Omar%20Akash%2091_62414-IJAER%20ok%201501-1505.pdf
http://eprints.utem.edu.my/id/eprint/22848/
https://www.ripublication.com/ijaer18/ijaerv13n2_91.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utem.eprints.22848
record_format eprints
spelling my.utem.eprints.228482021-08-24T13:56:45Z http://eprints.utem.edu.my/id/eprint/22848/ Fuzzy Distance Measure Based Affinity Propagation Clustering Al-Akash, Omar Mahmoud Nayef Syed Ahmad, Sharifah Sakinah Azmi, Mohd Sanusi Q Science (General) QA76 Computer software Affinity Propagation (AP) is an effective algorithm that find exemplars repeatedly exchange real valued messages between pairs of data points. AP uses the similarity between data points to calculate the messages. Hence, the construction of similarity is essential in the AP algorithm. A common choice for similarity is the negative Euclidean distance. However, due to the simplicity of Euclidean distance, it cannot capture the real structure of data. Furthermore, Euclidean distance is sensitive to noise and outliers such that the performance of the AP might be degraded. Therefore, researchers have intended to utilize different similarity measures to analyse the performance of AP. nonetheless, there is still a room to enhance the performance of AP clustering. A clustering method called fuzzy based Affinity propagation (F-AP) is proposed, which is based on a fuzzy similarity measure. Experiments shows the efficiency of the proposed F-AP, experiments is performed on UCI dataset. Results shows a promising improvement on AP. Research India Publications 2018 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/22848/2/non-indeks%20Omar%20Akash%2091_62414-IJAER%20ok%201501-1505.pdf Al-Akash, Omar Mahmoud Nayef and Syed Ahmad, Sharifah Sakinah and Azmi, Mohd Sanusi (2018) Fuzzy Distance Measure Based Affinity Propagation Clustering. International Journal Of Applied Engineering Research, 13 (2). pp. 1501-1505. ISSN 0973-4562 https://www.ripublication.com/ijaer18/ijaerv13n2_91.pdf
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic Q Science (General)
QA76 Computer software
spellingShingle Q Science (General)
QA76 Computer software
Al-Akash, Omar Mahmoud Nayef
Syed Ahmad, Sharifah Sakinah
Azmi, Mohd Sanusi
Fuzzy Distance Measure Based Affinity Propagation Clustering
description Affinity Propagation (AP) is an effective algorithm that find exemplars repeatedly exchange real valued messages between pairs of data points. AP uses the similarity between data points to calculate the messages. Hence, the construction of similarity is essential in the AP algorithm. A common choice for similarity is the negative Euclidean distance. However, due to the simplicity of Euclidean distance, it cannot capture the real structure of data. Furthermore, Euclidean distance is sensitive to noise and outliers such that the performance of the AP might be degraded. Therefore, researchers have intended to utilize different similarity measures to analyse the performance of AP. nonetheless, there is still a room to enhance the performance of AP clustering. A clustering method called fuzzy based Affinity propagation (F-AP) is proposed, which is based on a fuzzy similarity measure. Experiments shows the efficiency of the proposed F-AP, experiments is performed on UCI dataset. Results shows a promising improvement on AP.
format Article
author Al-Akash, Omar Mahmoud Nayef
Syed Ahmad, Sharifah Sakinah
Azmi, Mohd Sanusi
author_facet Al-Akash, Omar Mahmoud Nayef
Syed Ahmad, Sharifah Sakinah
Azmi, Mohd Sanusi
author_sort Al-Akash, Omar Mahmoud Nayef
title Fuzzy Distance Measure Based Affinity Propagation Clustering
title_short Fuzzy Distance Measure Based Affinity Propagation Clustering
title_full Fuzzy Distance Measure Based Affinity Propagation Clustering
title_fullStr Fuzzy Distance Measure Based Affinity Propagation Clustering
title_full_unstemmed Fuzzy Distance Measure Based Affinity Propagation Clustering
title_sort fuzzy distance measure based affinity propagation clustering
publisher Research India Publications
publishDate 2018
url http://eprints.utem.edu.my/id/eprint/22848/2/non-indeks%20Omar%20Akash%2091_62414-IJAER%20ok%201501-1505.pdf
http://eprints.utem.edu.my/id/eprint/22848/
https://www.ripublication.com/ijaer18/ijaerv13n2_91.pdf
_version_ 1709671910108823552
score 13.211869

Similar Items