Feature Selection Method Based On Hybrid Filter-Metaheuristic Wrapper Approach
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Date
2020-11
Authors
Neesha Jothi
Journal Title
Journal ISSN
Volume Title
Publisher
Universiti Sains Malaysia
Abstract
High dimension data are often associated with redundant features and there exist many information-theoretic approaches used to select the most relevant set of features and to reduce the feature size. The three most significant approaches are filter, wrap- per, and embedded approaches. Most filter approaches fail to identify the individual contribution of every feature in each set of features in achieving an optimal feature subset. While the wrapper approaches encounter problems from complex interactions among features and stagnation in local optima. To address, these drawbacks, this study investigates filter and wrapper approaches to develop effective hybrid approaches for
feature selection.
Description
Keywords
Feature Selection Method Based On Hybrid , Filter-Metaheuristic Wrapper Approach