Bio-Inspired Credit Risk Analysis: Computational Intelligence with Support Vector Machines

By Lean Yu, Shouyang Wang, Kin Keung Lai

Book Overview

Part I Credit Risk Analysis with Computational Intelligence: An Analytical Survey: Credit Risk Analysis with Computational Intelligence: A Review, - Part II Unitary SVM Models with Optimal Parameter Selection for Credit Risk Evaluation: Credit Risk Assessment Using a Nearest-Point-Algorithm-based SVM with Design of Experiment for Parameter Selection, - Credit Risk Evaluation Using SVM with Direct Search for Parameter Selection, - Part III Hybridizing SVM and Other Computational Intelligent Techniques for Credit Risk Analysis: Hybridizing Rough Sets and SVM for Credit Risk Evaluation, - A Least Squares Fuzzy SVM Approach to Credit Risk Assessment, - Evaluating Credit Risk with a Bilateral-Weighted Fuzzy SVM Model, - Evolving Least Squares SVM for Credit Risk Analysis, - Part IV SVM Ensemble Learning for Credit Risk Analysis: Credit Risk Evaluation Using a Multistage Credit Risk Analysis with a SVM-based Metamodeling Ensemble Approach, - An Evolutionary-Programming-Based Knowledge Ensemble Model for Business Credit Risk Analysis, - An Intelligent-Agent-Based Multicriteria Fuzzy Group Decision Making Model for Credit Risk A

• Format: Hardcover
• Language: English
• ISBN: 3540778020
• ISBN13: 9783540778028
• Release Date: June 2008
• Publisher: Springer
• Length: 244 Pages
• Weight: 1.20 lbs.
• Dimensions: 0.6" x 6.1" x 9.2"