Unbalanced Data Classification Based on Hesitant Fuzzy Decision Tree

In order to optimize the classification effect of unbalanced data,an improved fuzzy decision tree algorithm is proposed combining the hesitant fuzzy set theory and the decision tree algorithm.The unbalanced data is oversampled by the SMOTE algorithm,the cluster center point of each attribute is obta...

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Bibliographic Details
Published in:	Ji suan ji gong cheng Vol. 45; no. 8; pp. 75 - 79,91
Main Author:	ZHANG Xu, ZHOU Xinzhi, ZHAO Chengping, SHAO Lun
Format:	Journal Article
Language:	Chinese English
Published:	Editorial Office of Computer Engineering 01.08.2019
Subjects:	unbalanced data\|hesitant fuzzy sets\|hesitant fuzzy decision tree(hfdt)\|k-means clustering\|fuzzy id3 algorithm
ISSN:	1000-3428
Online Access:	Get full text
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