Efficient Diagnosis of Liver Disease using Support Vector Machine Optimized with Crows Search Algorithm

Devikanniga, D. and Ramu, Arulmurugan and Haldorai, Anandakumar (2020) Efficient Diagnosis of Liver Disease using Support Vector Machine Optimized with Crows Search Algorithm. EAI Endorsed Transactions on Energy Web, 7: e10. ISSN 2032-944X

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Abstract

The early and accurate prediction of liver disease in patients is still a challenging task among medical practitioners even with latest advanced technologies. The support vector machines are widely used in medical domain. It has proved its efficiency on producing good diagnostic parameters. These results can be further improved by optimizing the hyperparameters of support vector machines. The proposed work is based on optimizing support vector machines with crow search algorithm. This optimized support vector machine classifier (CSA-SVM) is used for accurate diagnosis of Indian liver disease data. The various similar state of art algorithms are taken for comparison with proposed approach to prove its efficient. The performance of CSA-SVM is found to be outstanding among all other approaches in terms of all metrics taken for comparison. It has yielded the classification accuracy of 99.49%.

Item Type: Article
Uncontrolled Keywords: Crow search algorithm, liver disease, sequential minimal optimization, support vector machine
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 16 Sep 2020 14:00
Last Modified: 16 Sep 2020 14:00
URI: https://eprints.eudl.eu/id/eprint/378

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