Prediction of Bank Loan Type Using Naive Bayesian Classification

Abstract

Data Mining is the process of storing through large amount of data and picking out relevant information. Classification can be used as in the form of data analysis that can be used to extract models describing the important data classes. Classification is the task to identify the class labels for instances based on a set of features (attributes). As Myanmar is the rice-mart of the world, agricultural remains the vital sector of the economy and measures has been taken to increase productivity of paddy and other crops. It needs to predict the possibility of default of a potential counterparty before they extend a loan to the growers. In this paper, we proposed a bank loan-type prediction system for Myanmar agriculture development Bank by using Bayesian classification. Our system's performance results are also discussed in this paper.