The New and Computationally Efficient MIL-SOM Algorithm : Potential Benefits for Visualization and Analysis of a Large-Scale High-Dimensional Clinically Acquired Geographic Data
Joint Authors
Achenie, Luke E. K.
Oyana, Tonny J.
Heo, Joon
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-03-19
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
The objective of this paper is to introduce an efficient algorithm, namely, the mathematically improved learning-self organizing map (MIL-SOM) algorithm, which speeds up the self-organizing map (SOM) training process.
In the proposed MIL-SOM algorithm, the weights of Kohonen’s SOM are based on the proportional-integral-derivative (PID) controller.
Thus, in a typical SOM learning setting, this improvement translates to faster convergence.
The basic idea is primarily motivated by the urgent need to develop algorithms with the competence to converge faster and more efficiently than conventional techniques.
The MIL-SOM algorithm is tested on four training geographic datasets representing biomedical and disease informatics application domains.
Experimental results show that the MIL-SOM algorithm provides a competitive, better updating procedure and performance, good robustness, and it runs faster than Kohonen’s SOM.
American Psychological Association (APA)
Oyana, Tonny J.& Achenie, Luke E. K.& Heo, Joon. 2012. The New and Computationally Efficient MIL-SOM Algorithm : Potential Benefits for Visualization and Analysis of a Large-Scale High-Dimensional Clinically Acquired Geographic Data. Computational and Mathematical Methods in Medicine،Vol. 2012, no. 2012, pp.1-14.
https://search.emarefa.net/detail/BIM-490244
Modern Language Association (MLA)
Oyana, Tonny J.…[et al.]. The New and Computationally Efficient MIL-SOM Algorithm : Potential Benefits for Visualization and Analysis of a Large-Scale High-Dimensional Clinically Acquired Geographic Data. Computational and Mathematical Methods in Medicine No. 2012 (2012), pp.1-14.
https://search.emarefa.net/detail/BIM-490244
American Medical Association (AMA)
Oyana, Tonny J.& Achenie, Luke E. K.& Heo, Joon. The New and Computationally Efficient MIL-SOM Algorithm : Potential Benefits for Visualization and Analysis of a Large-Scale High-Dimensional Clinically Acquired Geographic Data. Computational and Mathematical Methods in Medicine. 2012. Vol. 2012, no. 2012, pp.1-14.
https://search.emarefa.net/detail/BIM-490244
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-490244