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Interactive evolutionary approaches to multiobjective feature selection
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Date
2018-05-01
Author
ÖZMEN, müberra
Karakaya, Gülşah
KÖKSALAN, MUSTAFA MURAT
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In feature selection problems, the aim is to select a subset of features to characterize an output of interest. In characterizing an output, we may want to consider multiple objectives such as maximizing classification performance, minimizing number of selected features or cost, etc. We develop a preference-based approach for multiobjective feature selection problems. Finding all Pareto-optimal subsets may turn out to be a computationally demanding problem and we still would need to select a solution. Therefore, we develop interactive evolutionary approaches that aim to converge to a subset that is highly preferred by the decision maker (DM). We test our approaches on several instances simulating DM preferences by underlying preference functions and demonstrate that they work well.
Subject Keywords
Management of Technology and Innovation
,
Management Science and Operations Research
,
Strategy and Management
,
Business and International Management
,
Computer Science Applications
URI
https://hdl.handle.net/11511/37819
Journal
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
DOI
https://doi.org/10.1111/itor.12428
Collections
Department of Business Administration, Article
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m. ÖZMEN, G. Karakaya, and M. M. KÖKSALAN, “Interactive evolutionary approaches to multiobjective feature selection,”
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
, pp. 1027–1052, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/37819.