Decision Tree-Based Extension Strategy Generation and Knowledge Discovery

DOI

10.2991/icmse-18.2018.133How to use a DOI?

Keywords

decision tree; extension transformation; extension strategy analysis; classification

Abstract

To overcome the drawbacks of both traditional extension strategy analysis methods and traditional decision tree classification, an extension strategy analysis method based on decision tree classification was proposed. First, original data were obtained through basic-element theory and optimized by extension data pre-processing. Second, optimized data were statically classified by dependent function, and an extension decision tree was constructed according to the results of information entropy and information gain calculations. Then, through extension strategy analysis, extension strategies were generated. Finally, the validity and feasibility of this method were proved by an experiment.

Copyright

© 2018, 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  - Kaijie Wang
AU  - Libo Xu
AU  - Jinghui Li
PY  - 2018/05
DA  - 2018/05
TI  - Decision Tree-Based Extension Strategy Generation and Knowledge Discovery
BT  - Proceedings of the 2018 8th International Conference on Manufacturing Science and Engineering (ICMSE 2018)
PB  - Atlantis Press
SP  - 722
EP  - 729
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmse-18.2018.133
DO  - 10.2991/icmse-18.2018.133
ID  - Wang2018/05
ER  -