Bankruptcy prediction using memetic algorithm

dc.contributor.author Naveen, Nekuri
dc.contributor.author Rao, Mamillapalli Chilaka
dc.date.accessioned 2022-03-27T05:58:33Z
dc.date.available 2022-03-27T05:58:33Z
dc.date.issued 2016-01-01
dc.description.abstract This paper proposes a new memetic algorithm using Cuckoo search algorithm and Particle Swarm Optimization algorithm. Training set is fed to the proposed method to get trained. The effectiveness of the proposed method is evaluated using three bankruptcy viz., Spanish banks, Turkish banks and US banks and three benchmark datasets namely, Iris, WBC and Wine datasets. We performed 10 Fold Cross Validation testing and observed that the results obtained by the proposed method in terms of the sensitivity, specificity and accuracy are encouraging when compared to that of the baseline decision tree.
dc.identifier.citation Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). v.10053 LNAI
dc.identifier.issn 03029743
dc.identifier.uri 10.1007/978-3-319-49397-8_13
dc.identifier.uri http://link.springer.com/10.1007/978-3-319-49397-8_13
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/8982
dc.subject Bankruptcy prediction
dc.subject Classification
dc.subject Cuckoo search algorithm
dc.subject Data mining
dc.subject Memetic algorithm
dc.subject Particle swarm optimization
dc.title Bankruptcy prediction using memetic algorithm
dc.type Book Series. Conference Paper
dspace.entity.type
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