Title :
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
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;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2013 International Conference on
Conference_Location :
Tianjin
DOI :
10.1109/ICMLC.2013.6890506
