Bio-Inspired Credit Risk Analysis: Computational Intelligence with Support Vector Machines
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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 Analysis.
Format:Paperback
Language:English
ISBN:3642096557
ISBN13:9783642096556
Release Date:October 2010
Publisher:Springer
Length:244 Pages
Weight:0.82 lbs.
Dimensions:0.6" x 6.1" x 9.2"
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