Credit Evaluation Model For Banks Using Data Mining Techniques

4296 Words Jul 19th, 2015 18 Pages
Credit Evaluation Model for Banks Using Data Mining Techniques
By Sharan Brahmanapally, Bachelor of Technology

A Project submitted in Partial
Fulfillment of the Requirements
For the Degree of
Master of Science
In the field of Industrial Engineering

Advisory Committee:
Dr. Hoo Sang Ko

Graduate School
Southern Illinois University Edwardsville
August, 2015

TABLE OF CONTENTS
TABLE OF CONTENTS ii
LIST OF FIGURES iii
LIST OF TABLES iii
ABSTRACT iv
CHAPTER 1 1
INTRODUCTION 1
1.1 Introduction 1
1.1.1 Decision Process for Credit Evaluation 3
1.2 Problem Statement 4
1.3 Aim of the Project 4
1.4 Objectives of the Project 5
CHAPTER 2 6
LITERATURE REVIEW 6
2.1 Introduction 6
2.2 Theoretical Background 6
2.2.1 Decision Trees 6
2.2.2 Support Vector Machine 8
2.2.3 Logistic Regression 9
2.2.4 Ensemble Methods 10
CHAPTER 3 13
METHODOLOGY AND EXPERIMENTS 13
3.1 Data Selection and Data Preprocessing 13
3.2.1 Missing Values 14
3.2.2 Data Pre-processing 14
3.3 Results 15
3.3.1 Performance Estimation 17
CHAPTER 4 20
CONCLUSION 20
REFERENCES 21
APPENDIX 22
Outputs of Models 22

LIST OF FIGURES

Figure 1: Logistic Regression Curve 10

LIST OF TABLES

Table 1: Data Set for Analysis 13
Table 2: Area under ROC Curve 17
Table 3: Results by J48 18
Table 4: Results by CART 18
Table 5: Results by Logistic Regression 18
Table 6: Results by Support Vector Machine 18
Table 7: Results by Bagging 18
Table 8: Results by Boosting 18
Table 9: Classification Table with Success Rate 19…
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