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Aldehim, Ghadah, De La Iglesia, Beatriz 
ORCID: https://orcid.org/0000-0003-2675-5826 and Wang, Wenjia
(2014)
Heuristic Ensemble of Filters for Reliable Feature Selection.
In: International Conference on Pattern Recognition Applications and Methods (ICPRAM 2014), 2014-05-10.
Abstract
Feature selection has become ever more important in data mining in recent years due to the rapid increase in the dimensionality of data. Filters are preferable in practical applications as they are much faster than wrapper based approaches, but their reliability and consistency vary considerably on different data and yet no rule exists to indicate which one should be used for a particular given dataset. In this paper, we propose a heuristic ensemble approach that combines multiple filters with heuristic rules to improve the overall performance. It consists of two types of filters: subset filters and ranking filters, and a heuristic consensus algorithm. The experimental results demonstrate that our ensemble algorithm is more reliable and effective than individual filters as the features selected by the ensemble consistently achieve better accuracy for typical classifiers on various datasets.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | feature selection,filter,ensemble |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Data Science and Statistics Faculty of Medicine and Health Sciences > Research Centres > Business and Local Government Data Research Centre (former - to 2023) Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre |
| Depositing User: | Pure Connector |
| Date Deposited: | 08 Sep 2014 12:46 |
| Last Modified: | 19 Apr 2023 01:31 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/49929 |
| DOI: |
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