Interpretable knowledge discovery from data with DC*

被引：0

作者：

Lucarelli, Marco ^{[1
]}

Castiello, Ciro ^{[1
]}

Fanelli, Anna M. ^{[1
]}

Mencar, Corrado ^{[1
]}

机构：

[1] Univ Bari A Moro, Dept Informat, Bari, Italy

来源：

PROCEEDINGS OF THE 2015 CONFERENCE OF THE INTERNATIONAL FUZZY SYSTEMS ASSOCIATION AND THE EUROPEAN SOCIETY FOR FUZZY LOGIC AND TECHNOLOGY | 2015年 / 89卷

关键词：

DC*; Knowledge discovery from data; Interpretability; sleep-related breathing disorders;

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：

We present DC* (Double Clustering with A*) as an information granulation method specifically suited for deriving interpretable knowledge from data. DC* is based on two main clustering stages: the first is devoted to compressing multi-dimensional data into few prototypes that grab the main relationships among data; the second is aimed at finding a proper fuzzy granulation of each input feature so that the relations among data can be linguistically described in terms of fuzzy classification rules. We applied DC* as a stage in a knowledge discovery process, aimed at finding interpretable diagnostic rules for sleep-related breathing disorders.

引用

页码：815 / 822

页数：8

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