A Novel Approach for Data Classification Using Neutrosophic Entropy

被引：2

作者：

Bhutani, Kanika ^{[1
]}

Aggarwal, Swati ^{[2
]}

机构：

[1] NIT Kurukshetra, Dept Comp Engn, Kurukshetra, Haryana, India

[2] NSIT, COE, Dwarka, India

来源：

SYSTEM AND ARCHITECTURE, CSI 2015 | 2018年 / 732卷

关键词：

Classification; Fuzzy probability; Fuzzy entropy; Neutrosophic probability; Neutrosophic entropy; FUZZY; SIMILARITY; SETS;

D O I：

10.1007/978-981-10-8533-8_29

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Fuzzy classification is very necessary because it has the ability to use interpretable rules. It has got control over the limitations of crisp rule-based classification. This paper mainly deals with classification using fuzzy probability and Neutrosophic probability. Classification based on Neutrosophic probability employs Neutrosophic logic, Neutrosophic probability, and Neutrosophic entropy for its working and is compared with classification based on fuzzy probability on the basis of parameters such as probability and ambiguity in the results. Classification based on fuzzy and Neutrosophic probabilities is implemented on appendicitis dataset from knowledge extraction based on evolutionary learning.

引用

页码：305 / 317

页数：13

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