Random forests ensemble classifier trained with data resampling strategy to improve cardiac arrhythm...
Random forests ensemble classifier trained with data resampling strategy to improve cardiac arrhythmia diagnosis
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Publisher
United States: Elsevier Ltd
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Language
English
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Publisher
United States: Elsevier Ltd
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Contents
Abstract Supervised classification algorithms are commonly used in the designing of computer-aided diagnosis systems. In this study, we present a resampling strategy based Random Forests (RF) ensemble classifier to improve diagnosis of cardiac arrhythmia. Random forests is an ensemble classifier that consists of many decision trees and outputs the...
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Full title
Random forests ensemble classifier trained with data resampling strategy to improve cardiac arrhythmia diagnosis
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TN_cdi_proquest_miscellaneous_876236346
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_876236346
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ISSN
0010-4825
E-ISSN
1879-0534
DOI
10.1016/j.compbiomed.2011.03.001
