Preserving the topology of self-organizing maps for data analysis: A review
In Kohonen's Self-Organizing Maps (SOM) algorithm, preserving the map structure to represent the real input patterns appears to be a significant process. Misinterpretation of the training samples can lead to failure in identifying the important features that may affect the outcomes generated by...
| Main Authors: | , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IOP Publishing
2020
|
| Subjects: | |
| Online Access: | https://umpir.ump.edu.my/id/eprint/29756/ |
| _version_ | 1848827287044096000 |
|---|---|
| author | Bariah, Yusob Zuriani, Mustaffa Siti Mariyam, Shamsuddin |
| author_facet | Bariah, Yusob Zuriani, Mustaffa Siti Mariyam, Shamsuddin |
| author_sort | Bariah, Yusob |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | In Kohonen's Self-Organizing Maps (SOM) algorithm, preserving the map structure to represent the real input patterns appears to be a significant process. Misinterpretation of the training samples can lead to failure in identifying the important features that may affect the outcomes generated by the SOM model. This paper presents detail explanation on SOM learning algorithm and its applications. Some issues related to SOM's architecture are also discussed, namely the formulation of training data from input samples, and the Best Matching Unit (BMU) identification for better visualization of large datasets, and improvement made to the SOM algorithm. |
| first_indexed | 2025-11-15T03:58:19Z |
| format | Conference or Workshop Item |
| id | ump-29756 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:58:19Z |
| publishDate | 2020 |
| publisher | IOP Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-297562025-10-23T03:13:46Z https://umpir.ump.edu.my/id/eprint/29756/ Preserving the topology of self-organizing maps for data analysis: A review Bariah, Yusob Zuriani, Mustaffa Siti Mariyam, Shamsuddin QA76 Computer software In Kohonen's Self-Organizing Maps (SOM) algorithm, preserving the map structure to represent the real input patterns appears to be a significant process. Misinterpretation of the training samples can lead to failure in identifying the important features that may affect the outcomes generated by the SOM model. This paper presents detail explanation on SOM learning algorithm and its applications. Some issues related to SOM's architecture are also discussed, namely the formulation of training data from input samples, and the Best Matching Unit (BMU) identification for better visualization of large datasets, and improvement made to the SOM algorithm. IOP Publishing 2020 Conference or Workshop Item PeerReviewed pdf en cc_by https://umpir.ump.edu.my/id/eprint/29756/1/36.%20Preserving%20the%20Topology%20of%20Self-Organizing%20Maps%20for%20Data%20Analysis-%20A%20Review.pdf Bariah, Yusob and Zuriani, Mustaffa and Siti Mariyam, Shamsuddin (2020) Preserving the topology of self-organizing maps for data analysis: A review. In: IOP Conference Series: Materials Science and Engineering. The 6th International Conference on Software Engineering & Computer Systems , 25-27 September 2019 , Pahang, Malaysia. pp. 1-6., 769 (012004). ISSN 1757-8981 (Print), 1757-899X (Online) (Published) https://doi.org/10.1088/1757-899X/769/1/012004 |
| spellingShingle | QA76 Computer software Bariah, Yusob Zuriani, Mustaffa Siti Mariyam, Shamsuddin Preserving the topology of self-organizing maps for data analysis: A review |
| title | Preserving the topology of self-organizing maps for data analysis: A review |
| title_full | Preserving the topology of self-organizing maps for data analysis: A review |
| title_fullStr | Preserving the topology of self-organizing maps for data analysis: A review |
| title_full_unstemmed | Preserving the topology of self-organizing maps for data analysis: A review |
| title_short | Preserving the topology of self-organizing maps for data analysis: A review |
| title_sort | preserving the topology of self-organizing maps for data analysis: a review |
| topic | QA76 Computer software |
| url | https://umpir.ump.edu.my/id/eprint/29756/ https://umpir.ump.edu.my/id/eprint/29756/ |