Effective Evolutionary Multilabel Feature Selection under a Budget Constraint
Joint Authors
Lee, Jaesung
Seo, Wangduk
Kim, Dae-Won
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-03-07
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Multilabel feature selection involves the selection of relevant features from multilabeled datasets, resulting in improved multilabel learning accuracy.
Evolutionary search-based multilabel feature selection methods have proved useful for identifying a compact feature subset by successfully improving the accuracy of multilabel classification.
However, conventional methods frequently violate budget constraints or result in inefficient searches due to ineffective exploration of important features.
In this paper, we present an effective evolutionary search-based feature selection method for multilabel classification with a budget constraint.
The proposed method employs a novel exploration operation to enhance the search capabilities of a traditional genetic search, resulting in improved multilabel classification.
Empirical studies using 20 real-world datasets demonstrate that the proposed method outperforms conventional multilabel feature selection methods.
American Psychological Association (APA)
Lee, Jaesung& Seo, Wangduk& Kim, Dae-Won. 2018. Effective Evolutionary Multilabel Feature Selection under a Budget Constraint. Complexity،Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1133573
Modern Language Association (MLA)
Lee, Jaesung…[et al.]. Effective Evolutionary Multilabel Feature Selection under a Budget Constraint. Complexity No. 2018 (2018), pp.1-14.
https://search.emarefa.net/detail/BIM-1133573
American Medical Association (AMA)
Lee, Jaesung& Seo, Wangduk& Kim, Dae-Won. Effective Evolutionary Multilabel Feature Selection under a Budget Constraint. Complexity. 2018. Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1133573
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1133573