Data mining technology based on rough set and genetic algorithm under large data environment

DOI

10.2991/meita-16.2017.117How to use a DOI?

Keywords

Data mining; rough set; genetic algorithm; association rule mining

Abstract

New requirements drive the birth of new technologies. Data analysis is the foundation of scientific research, many scientific research is based on data collection and analysis. This paper introduces the basic theory of classical rough set, which is based on the equivalence relation, and uses an upper and lower approximation to represent an imprecise concept. Property reduction is one of the core problems of rough set theory. The heuristic algorithm find attribute reduction is an effective way to solve the problem. On the basis of rough reduction algorithm based on rough set theory, this paper makes a preliminary realization of the problem based on rough set theory, which includes: data discretization, knowledge reduction, rule extraction. The coarsening algorithm based on rough set theory for attribute reduction is essentially a range of attribute values which narrow to wide process.

Copyright

© 2017, 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  - Liping Wang
PY  - 2017/02
DA  - 2017/02
TI  - Data mining technology based on rough set and genetic algorithm under large data environment
BT  - Proceedings of the 2016 2nd International Conference on Materials Engineering and Information Technology Applications (MEITA 2016)
PB  - Atlantis Press
SP  - 561
EP  - 565
SN  - 2352-5401
UR  - https://doi.org/10.2991/meita-16.2017.117
DO  - 10.2991/meita-16.2017.117
ID  - Wang2017/02
ER  -