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Interactive Approaches to Multi-objective Feature Selection
Date
2017-10-25
Author
Özmen, Müberra
Karakaya, Gülşah
Köksalan, Mustafa Murat
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https://hdl.handle.net/11511/72230
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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 multi-objective 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 event...
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In this study, we develop interactive approaches to find a satisfactory alternative of a decision maker (DM) having a quasiconvex preference function where the alternative set changes progressively. In this environment, we keep searching the available set of alternatives and estimating the preference function of the DM. As new alternatives emerge, we make better use of the available preference information and eventually converge to a preferred alternative of the DM. We test our approaches on biobjective, mu...
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In this study, interactive approaches for sorting alternatives evaluated on multiple criteria are developed. The possible category ranges of alternatives are defined by mathematical models iteratively under the assumption that the preferences of the decision maker (DM) are consistent with an additive utility function. Simulation-based and model-based parameter generation methods are proposed to hypothetically assign the alternatives to categories. A practical approach to solve the incompatibility problem of...
Interactive approaches for multiobjective decision making.
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M. Özmen, G. Karakaya, and M. M. Köksalan, “Interactive Approaches to Multi-objective Feature Selection,” 2017, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/72230.