Conceptual Approach to Predict Loan Defaults Using Decision Trees

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Author(s): Syed Muzamil Basha (Sri Krishna College of Engineering and Technology, India), Dharmendra Singh Rajput (VIT University, India)and N. Ch. S. N. Iyengar (Sreenidhi Institute of Science and Technology, India)
Copyright: 2019
Pages: 14
Source title: Sentiment Analysis and Knowledge Discovery in Contemporary Business
Source Author(s)/Editor(s): Dharmendra Singh Rajput (VIT University, India), Ramjeevan Singh Thakur (Maulana Azad National Institute of Technology, India)and S. Muzamil Basha (VIT University, India)
DOI: 10.4018/978-1-5225-4999-4.ch009

Keywords: Business and Organizational Research / Business Science Reference / Knowledge Discovery / Library & Information Science

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Abstract

In this chapter, the authors show how to build a decision tree from given real-time data. They interpret the output of decision tree by learning decision tree classifier using really recursive greedy algorithm. Feature selection is made based on classification error using the algorithm called feature split selection algorithm (FSSA), with all different possible stopping conditions for splitting. The authors perform prediction with decision trees using decision tree prediction algorithm (DTPA), followed by multiclass predictions and their probabilities. Finally, they perform splitting procedure on real continuous value input using threshold split selection algorithm (TSSA).

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Conceptual Approach to Predict Loan Defaults Using Decision Trees

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