Information theoretic clustering used for two items loan management system

Author

Shuo Wang ; Jianjian Wang ; Jin-E Li

Author_Institution

Fac. of Math. & Comput. Sci., Hebei Univ., Baoding, China

Volume

01

fYear

2013

fDate

14-17 July 2013

Firstpage

438

Lastpage

442

Abstract

Clustering is an effective machine learning method for classification and decision making. This paper builds a system model for loan management and incorporates the information clustering algorithm into this system. This clustering algorithm describes the cluster memberships with a non-parametric mutual information estimate between cluster assignment and data distribution. It can improve the classification accuracy and efficiency.

Keywords

data warehouses; decision making; information theory; learning (artificial intelligence); pattern classification; pattern clustering; classification accuracy; classification efficiency; cluster assignment; cluster memberships; data distribution; data warehouse; decision making; information theoretic clustering algorithm; machine learning method; minimum spanning tree; nonparametric mutual information estimate; system model; two items loan management system; Abstracts; Cancer; Data mining; History; Iris; Schedules; Data warehouse; Decision methods; Information theoretic clustering; Minimum spanning tree; Two items loan management system;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics (ICMLC), 2013 International Conference on

Conference_Location

Tianjin

Type

conf

DOI

10.1109/ICMLC.2013.6890506

Filename

6890506