Some results of classification problem by Bayesian method and application in credit operation

ABSTRACT

This study proposes some results in classifying by Bayesian method. There are upper and lower bounds of the Bayes error as well as its determination in case of one dimension and multi-dimensions. Based on the proposals for estimating of probability density functions, calculating the Bayes error and determining the prior probability, we establish an algorithm to evaluate ability of customers to pay debts at banks. This algorithm has been performed by the Matlab procedure that can be applied well with real data. The proposed algorithm is tested by the real application at a bank in Viet Nam that obtains the best results in comparing with the existing approaches.

Keywords:

• Bayesian method
• classification
• error
• credit operation
• prior probability

Disclosure statement

No potential conflict of interest was reported by the author.

Additional information

Notes on contributors

Tai Vovan

Tai Vovan received the Ph.D. degree in theory of probability and statistical mathematics in 2011. He has worked in Can Tho University, Viet Nam, since 1997. His research interests include statistical pattern recognition (classification problem and cluster analysis) and fuzzy time series and their applications in data mining. He has published over 20 papers about these subjects.