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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Vydané v:	Ji suan ji gong cheng Ročník 45; číslo 8; s. 75 - 79,91
Hlavný autor:	ZHANG Xu, ZHOU Xinzhi, ZHAO Chengping, SHAO Lun
Médium:	Journal Article
Jazyk:	Chinese English
Vydavateľské údaje:	Editorial Office of Computer Engineering 01.08.2019
Predmet:	unbalanced data|hesitant fuzzy sets|hesitant fuzzy decision tree(hfdt)|k-means clustering|fuzzy id3 algorithm
ISSN:	1000-3428
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