A Neighborhood Rough Sets-Based Attribute Reduction Method Using Lebesgue and Entropy Measures

A Neighborhood Rough Sets-Based Attribute Reduction Method Using Lebesgue and Entropy Measures

For continuous numerical data sets, neighborhood rough sets-based attribute reduction is an important step for improving classification performance. However, most of the traditional reduction algorithms can only handle finite sets, and yield low accuracy and high cardinality. In this paper, a novel...

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Bibliographic Details
Main Authors: Lin Sun, Lanying Wang, Jiucheng Xu, Shiguang Zhang
Format: Article
Language:English
Published: MDPI AG 2019-02-01
Series:Entropy
Subjects:
rough sets
neighborhood rough sets
attribute reduction
neighborhood entropy
Lebesgue measure
Online Access:https://www.mdpi.com/1099-4300/21/2/138

Internet

https://www.mdpi.com/1099-4300/21/2/138

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