Comparative analysis of PSO and ACO based feature selection techniques for medical data preservation
Joint Authors
Selvarajan, Dhanalakshmi
Abd al-Jabbar, Abd al-Sami
Ahmad, Irfan
Source
The International Arab Journal of Information Technology
Issue
Vol. 16, Issue 4 (31 Jul. 2019)6 p.
Publisher
Publication Date
2019-07-31
Country of Publication
Jordan
No. of Pages
6
Main Subjects
Information Technology and Computer Science
Abstract EN
Sensitive medical dataset consist of large number of disease attributes or features, not all these features are used for diagnosis.
In order to preserve the medical dataset it is not essential to perturb all the features before it is shared for mining purpose.
To reduce the computational cost and to increase the efficiency, in this work tried to use Ant Colony Optimization (ACO) for feature subset selection which is used to reduce the dimension and also compared with feature subset selection using Particle Swarm Optimization (PSO) which is also used to reduce the dimension.
Both the techniques are explored to reduce the dimension before applying preservation technique.
By using randomization method a known distribution is added to the reduced sensitive data before the data is sent to the miner.
The approach is analyzed using standard UCI medical datasets.
The result is analyzed based on classification accuracy using machine learning algorithms (Naïve Bayes, Decision Tree) build on the randomized dataset.
The experimental results show that the accuracy is maintained in the reduced perturbed datasets.
The results also show that ACO search based feature selection has more accuracy than PSO search based selection.
American Psychological Association (APA)
Selvarajan, Dhanalakshmi& Abd al-Jabbar, Abd al-Sami& Ahmad, Irfan. 2019. Comparative analysis of PSO and ACO based feature selection techniques for medical data preservation. The International Arab Journal of Information Technology،Vol. 16, no. 4.
https://search.emarefa.net/detail/BIM-854976
Modern Language Association (MLA)
Selvarajan, Dhanalakshmi…[et al.]. Comparative analysis of PSO and ACO based feature selection techniques for medical data preservation. The International Arab Journal of Information Technology Vol. 16, no. 4 (Jul. 2019).
https://search.emarefa.net/detail/BIM-854976
American Medical Association (AMA)
Selvarajan, Dhanalakshmi& Abd al-Jabbar, Abd al-Sami& Ahmad, Irfan. Comparative analysis of PSO and ACO based feature selection techniques for medical data preservation. The International Arab Journal of Information Technology. 2019. Vol. 16, no. 4.
https://search.emarefa.net/detail/BIM-854976
Data Type
Journal Articles
Language
English
Record ID
BIM-854976