Enhancing Decision Tree Performance in Credit Risk Classification and Prediction

  • Raymond Sunardi Oetama

Abstract

This study is focused on enhancing Decision Tree on its capabilities in classification as well as prediction. The capability of decision tree algorithm in classification outperforms its capability in prediction. The classification quality will be enhanced when it works with resampling techniques such as Adaboost.

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Published
2015-06-01
How to Cite
Oetama, R. (2015). Enhancing Decision Tree Performance in Credit Risk Classification and Prediction. Ultimatics : Jurnal Teknik Informatika, 7(1). https://doi.org/https://doi.org/10.31937/ti.v7i1.349