Genetic Algorithm Based Feature Subset Selection for Fetal State Classification
2015 ◽
Vol 2
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pp. 13
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Keyword(s):
Huge amount of data are available in the field of medicine which are used for diagnosing the diseases by analyzing them. Presently, prediction of diseases are made easier and accurate by employing various data mining techniques to extract information from these medical data. This paper presents an improved method of classifying the cardiotocogram (CTG) data using Multiclass Support Vector Machine (MSVM) through an optimized feature subset produced by Genetic Algorithm (GA). Various performance metrics have been evaluated and the experimental results exhibit improved classification performance when using optimized feature set comparing to the full feature set.
2011 ◽
Vol 7
(5)
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pp. 707-714
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2019 ◽
Vol 18
(03)
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pp. 1950020
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2015 ◽
Vol 11
(6)
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pp. 49
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2018 ◽
Vol 58
(1)
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pp. 139-167
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2015 ◽
Vol XL-1-W5
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pp. 651-656
2004 ◽
Vol 34
(1)
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pp. 60-67
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2017 ◽
Vol 70
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pp. 211-219
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