Personal Credit Scoring Based on Decision Tree C5.0 Algorithm

DOI

10.2991/emcs-17.2017.329How to use a DOI?

Keywords

Personal credit scoring; Decision tree; C50 algorithm

Abstract

There are some problems still exist in traditional individual credit assessment system. To solve the problems, an decision tree individual credit assessment model is proposed. Using SPSS Clementine data mining tool, the personal credit data is clustering analysis by decision tree C5.0 method. It is worse to class a customer as good when they are bad,than it is to class a customer as bad when they are good. It is discussed as the different proportion of loss.

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  - Shang Gao
AU  - Changbao Wang
PY  - 2017/03
DA  - 2017/03
TI  - Personal Credit Scoring Based on Decision Tree C5.0 Algorithm
BT  - Proceedings of the 2017 7th International Conference on Education, Management, Computer and Society (EMCS 2017)
PB  - Atlantis Press
SP  - 1729
EP  - 1734
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcs-17.2017.329
DO  - 10.2991/emcs-17.2017.329
ID  - Gao2017/03
ER  -