Random ensemble feature selection for land cover mapping

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dc.contributor.authorGidudu, Anthony
dc.contributor.authorBolanle, Abe T.
dc.contributor.authorMarwala, Tshilidzi
dc.date.accessioned2023-02-02T10:56:11Z
dc.date.available2023-02-02T10:56:11Z
dc.date.issued2009
dc.description.abstractRandom ensemble feature selection is a means through which diversity in ensemble systems is imposed by randomly selecting the features (bands) that constitute the base classifiers. This paper provides insight and discusses the interplay between the size of the resulting ensembles and the consequent classification accuracy. From the results, it was observed that classification accuracy increased more as the number of features per base classifier increases than as the number of base classifiers increases. That said however, classification accuracy was seen to increase with additional features up to a given limit beyond which increasing the number of features per base classifier did not significantly increase classification accuracy, a peaking effect probably due to Hughes phenomenon.en_US
dc.identifier.citationGidudu, A., Bolanle, A. T., & Marwala, T. (2009, July). Random ensemble feature selection for land cover mapping. In 2009 IEEE International Geoscience and Remote Sensing Symposium (Vol. 2, pp. II-840). IEEE.en_US
dc.identifier.urihttps://ieeexplore.ieee.org/abstract/document/5418226/
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/7474
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectRandomen_US
dc.subjectEnsembleen_US
dc.subjectFeatureen_US
dc.subjectSelectionen_US
dc.titleRandom ensemble feature selection for land cover mappingen_US
dc.typeArticleen_US
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