Rough set theory in discretization method based on genetic algorithm

DOI

10.2991/icmmcce-15.2015.403How to use a DOI?

Keywords

rough set, genetic algorithm, discretization.

Abstract

The rough set theory is a theory method. It is about incomplete research, uncertain expression of knowledge and data, knowledge and data discovery. It has been widely used in artificial intelligence, knowledge and data discovery, pattern recognition and classification, analysis and reasoning of imprecise data and find the potential knowledge, data mining. But the traditional rough set theory can only deal with discrete attributes in the database. While the vast majority of real database contains both discrete attributes and continuous attributes. Therefore, we must turn these continuous attributes into discrete. Aiming at this problem, this paper implements a discretization method based on genetic algorithm. It is using genetic algorithm to obtain the target, while keeping the original decision system under the condition of the indiscernibility relation and minimum break point set as the optimization target. Experimental results show that the discrete method using genetic algorithm is feasible.

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  - Lei Huang
PY  - 2015/12
DA  - 2015/12
TI  - Rough set theory in discretization method based on genetic algorithm
BT  - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.403
DO  - 10.2991/icmmcce-15.2015.403
ID  - Huang2015/12
ER  -