2026-06-27T02:43:10Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/5070 2021-12-13T02:48:16Z 1582963302567:1597824273898 user-ucsy

Credit Card Classification using Integration of Hierarchical Agglomerative Clustering and C4.5 Decision Tree Tun, May Thet Credit card classification is a systemfor credit card users which is used to assign eithera "good credit card ",which is likely to repayfinancial obligation, or a "bad credit card ",which has high possibility of defaulting onfinancial obligation. In a credit cardclassification, a credit card user’s data isusuallyassessed and evaluated, like his financial status,annual and monthly income, assets and liabilitiesand previous past payments to distinguish betweena “good” and a “bad” credit card for theuser.This paper presents the automatic credit cardclassification using integration of clustering andclassification algorithm. The goal of this paperistopredict the status of credit card such as good orbad. The empirical study between the integrationof hierarchical agglomerative algorithm and C 4.5decision tree algorithm and traditional C4.5decision tree algorithm areapplied based onStalog (“German credit data”) dataset from UCImachine learning repository. Then, the accuraciesof these two algorithms are compared. Accordingto experimental results, the integration ofhierarchical agglomerative clustering and C4.5decision tree could achieve higher accuracy thanthe traditional C4.5 decision tree. 2017-12-27 http://hdl.handle.net/20.500.12678/0000005070 https://meral.edu.mm/records/5070