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dc.contributor.author Qiang en_US
dc.contributor.author Richard en_US
dc.date.accessioned 2008-02-21T09:58:04Z
dc.date.available 2008-02-21T09:58:04Z
dc.date.issued 2008-04-01 en_US
dc.identifier http://dx.doi.org/10.1007/s10489-007-0058-y en_US
dc.identifier.citation Shen , Q & Jensen , R 2008 , ' Approximation-based feature selection and application for algae population estimation ' Applied Intelligence , vol 28 , no. 2 , pp. 167-181 . , 10.1007/s10489-007-0058-y en_US
dc.identifier.other PURE: 75485 en_US
dc.identifier.other dspace: 2160/504 en_US
dc.identifier.uri http://hdl.handle.net/2160/504
dc.description.abstract This paper presents a data-driven approach for feature selection to address the common problem of dealing with high-dimensional data. This approach is able to handle the real-valued nature of the domain features, unlike many existing approaches. This is accomplished through the use of fuzzy-rough approximations. The paper demonstrates the effectiveness of this research by proposing an estimator of algae populations, a system that approximates, given certain water characteristics, the size of algae populations. This estimator significantly reduces computer time and space requirements, decreases the cost of obtaining measurements and increases runtime efficiency, making itself more viable economically. By retaining only information required for the estimation task, the system offers higher accuracy than conventional estimators. Finally, the system does not alter the domain semantics, making any distilled knowledge human-readable. The paper describes the problem domain, architecture and operation of the system, and provides and discusses detailed experimentation. The results show that algae estimators using a fuzzy-rough feature selection step produce more accurate predictions of algae populations in general. en_US
dc.format.extent 15 en_US
dc.relation.ispartof Applied Intelligence en_US
dc.subject Feature evaluation and selection en_US
dc.subject Data-driven knowledge acquisition en_US
dc.subject Classification en_US
dc.subject Fuzzy-rough sets en_US
dc.subject Algae population estimation en_US
dc.title Approximation-based feature selection and application for algae population estimation en_US
dc.contributor.pbl Department of Computer Science en_US
dc.contributor.pbl Advanced Reasoning Group en_US


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