Bio-Inspired Credit Risk Computational Intelligence with Support Vector Machines

Table of Contents
Part I
Credit Risk Analysis with Computational Intelligence:
An Analytical Survey................................................................................. 1
1 Credit Risk Analysis with Computational Intelligence: A Review..... 3
Part II
Unitary SVM Models with Optimal Parameter Selection for Credit
Risk Evaluation........................................................................................ 25
2 Credit Risk Assessment Using a Nearest-Point-Algorithm-based
SVM with Design of Experiment for Parameter Selection.............. 27
3 Credit Risk Evaluation Using SVM with Direct Search for Parameter
Selection .......................................................................................... 41
Part III
Hybridizing SVM and Other Computational Intelligent Techniques
for Credit Risk Analysis .......................................................................... 57
4 Hybridizing Rough Sets and SVM for Credit Risk Evaluation........ 59
5 A Least Squares Fuzzy SVM Approach to Credit Risk Assessment 73
6 Evaluating Credit Risk with a Bilateral-Weighted Fuzzy SVM
Model.................................................................................................... 85
7 Evolving Least Squares SVM for Credit Risk Analysis ..................105
Part IV
SVM Ensemble Learning for Credit Risk Analysis............................133
8 Credit Risk Evaluation Using a Multistage SVM Ensemble Learning
Approach.............................................................................................135
9 Credit Risk Analysis with a SVM-based Metamodeling Ensemble
Approach.............................................................................................157
10 An Evolutionary-Programming-Based Knowledge Ensemble Model
for Business Credit Risk Analysis ................................................... 179
11 An Intelligent-Agent-Based Multicriteria Fuzzy Group Decision
Making Model for Credit Risk Analysis........................................ 197



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