Comparative Analysis of Feature Selection in Epilepsy Seizure Recognition Using Cuckoo, Gravitational Search and Bat Algorithm

8 Pages Posted: 2 Apr 2019

See all articles by Yash Upadhyaya

Yash Upadhyaya

University of Mumbai - Department of Computer Science and Engineering

Sharat Sachin

University of Mumbai - Department of Computer Science and Engineering

Abha Tripathi

University of Mumbai - Department of Computer Science and Engineering

Rachna Jain

Independent

Date Written: 2018

Abstract

While applying classification techniques on high dimensional data, we may not get satisfactory results due to a large number of attributes requiring lots of computational resources, and containing features which aren’t at all related to the response variable, hence making it difficult to be used for practical purposes. To deal with this problem swarm intelligence algorithms are used for selecting the best features for classification. In this paper, we have compared 3 swarm optimization algorithms for their feature selection abilities for recognition of epileptic seizures, which has high dimensional data with 179 features. The base classifiers used were Decision Tree, Random Forest and KNN whose performance was compared with and without feature selection. In our experimentation, we found that for each metric, a different combination of algorithms yielded the best results, for example, random forest with bat algorithm yielded 96.78% accuracy, 96.89% recall value which are the best results among other combinations.

Suggested Citation

Upadhyaya, Yash and Sachin, Sharat and Tripathi, Abha and Jain, Rachna, Comparative Analysis of Feature Selection in Epilepsy Seizure Recognition Using Cuckoo, Gravitational Search and Bat Algorithm (2018). International Journal of Information Systems & Management Science, Vol. 1, No. 1, 2018, Available at SSRN: https://ssrn.com/abstract=3363832

Yash Upadhyaya

University of Mumbai - Department of Computer Science and Engineering ( email )

India

Sharat Sachin (Contact Author)

University of Mumbai - Department of Computer Science and Engineering ( email )

India

Abha Tripathi

University of Mumbai - Department of Computer Science and Engineering ( email )

India

Rachna Jain

Independent ( email )

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