caa a22 4500 605469210 CHVBK 20210128100321.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s00500-014-1565-5 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1565-5 MODE: multiobjective differential evolution for feature selection and classifier ensemble [Elektronische Daten] [Utpal Sikdar, Asif Ekbal, Sriparna Saha] In this paper, we propose a multiobjective differential evolution (MODE)-based feature selection and ensemble learning approaches for entity extraction in biomedical texts. The first step of the algorithm concerns with the problem of automatic feature selection in a machine learning framework, namely conditional random field. The final Pareto optimal front which is obtained as an output of the feature selection module contains a set of solutions, each of which represents a particular feature representation. In the second step of our algorithm, we combine a subset of these classifiers using a MODE-based ensemble technique. Our experiments on three benchmark datasets namely GENIA, GENETAG and AIMed show the F-measure values of 76.75, 94.15 and 91.91%, respectively. Comparisons with the existing systems show that our proposed algorithm achieves the performance levels which are at par with the state of the art. These results also exhibit that our method is general in nature and because of this it performs well across the several domain of datasets. The key contribution of this work is the development of MODE-based generalized feature selection and ensemble learning techniques with the aim of extracting entities from the biomedical texts of several domains. Springer-Verlag Berlin Heidelberg, 2015 Sikdar Utpal Department of Computer Science and Engineering, Indian Institute of Technology Patna, Patna, Bihar, India aut Ekbal Asif Department of Computer Science and Engineering, Indian Institute of Technology Patna, Patna, Bihar, India aut Saha Sriparna Department of Computer Science and Engineering, Indian Institute of Technology Patna, Patna, Bihar, India aut Soft Computing Springer Berlin Heidelberg 19/12(2015-12-01), 3529-3549 1432-7643 19:12<3529 2015 19 500 https://doi.org/10.1007/s00500-014-1565-5 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1565-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Sikdar Utpal Department of Computer Science and Engineering, Indian Institute of Technology Patna, Patna, Bihar, India aut NATIONALLICENCE 700 1- Ekbal Asif Department of Computer Science and Engineering, Indian Institute of Technology Patna, Patna, Bihar, India aut NATIONALLICENCE 700 1- Saha Sriparna Department of Computer Science and Engineering, Indian Institute of Technology Patna, Patna, Bihar, India aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/12(2015-12-01), 3529-3549 1432-7643 19:12<3529 2015 19 500