fuzzycreator: A Python']Python-Based Toolkit for Automatically Generating and Analysing Data-Driven Fuzzy Sets

被引:0
作者
McCulloch, Josie [1 ]
机构
[1] Univ Nottingham, Lab Uncertainty Data & Decis Making LUCID, Sch Comp Sci, Nottingham, England
来源
2017 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE) | 2017年
关键词
INTERVAL TYPE-2; SYSTEMS; LOGIC;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a toolkit for automatic generation and analysis of fuzzy sets (FS) from data. Toolkits are vital for the wider dissemination, accessibility and implementation of theoretic work and applications on FSs. There are currently several toolkits in the literature that focus on knowledge representation and fuzzy inference, but there are few that focus on the automatic generation and comparison of FSs. As there are several methods of constructing FSs from data, it is important to have the tools to use these methods. This paper presents an open-source, python-based toolkit, named fuzzycreator, that facilitates the creation of both conventional and non-conventional (non-normal and non-convex) type-1, interval type-2 and general type-2 FSs from data. These FSs may then be analysed and compared through a series of tools and measures (included in the toolkit), such as evaluating their similarity and distance. An overview of the key features of the toolkit are given and demonstrations which provide rapid access to cutting-edge methodologies in FSs to both expert and non-expert users.
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页数:6
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