Interpretable knowledge discovery from data with DC*

DOI

10.2991/ifsa-eusflat-15.2015.115How to use a DOI?

Keywords

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

Abstract

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.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Marco Lucarelli
AU  - Ciro Castiello
AU  - Anna M. Fanelli
AU  - Corrado Mencar
PY  - 2015/06
DA  - 2015/06
TI  - Interpretable knowledge discovery from data with DC*
BT  - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 815
EP  - 822
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.115
DO  - 10.2991/ifsa-eusflat-15.2015.115
ID  - Lucarelli2015/06
ER  -