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| Prologue | |
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| Introduction to the Classification Problem | |
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| Decision making problematics | |
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| The classification problem | |
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| General outline of classification methods | |
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| The proposed methodological approach and the objectives of the book | |
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| Review of Classification Techniques | |
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| Introduction | |
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| Statistical and econometric techniques | |
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| Discriminant analysis | |
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| Logit and probit analysis | |
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| Non-parametric techniques | |
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| Neural networks | |
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| Machine learning | |
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| Fuzzy set theory | |
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| Rough sets | |
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| Multicriteria Decision Aid Classification Techniques | |
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| Introduction to multicriteria decision aid | |
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| Objectives and general framework | |
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| Brief historical review | |
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| Basic concepts | |
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| Methodological approaches | |
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| Multiobjective mathematical programming | |
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| Multiattribute utility theory | |
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| Outranking relation theory | |
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| Preference disaggregation analysis | |
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| MCDA techniques for classification problems | |
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| Techniques based on the direct interrogation of the decision maker | |
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| The AHP method | |
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| The ELECTRE TRI method | |
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| Other outranking classification methods | |
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| The preference disaggregation paradigm in classification problems | |
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| Preference Disaggregation Classification Methods | |
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| Introduction | |
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| The UTADIS method | |
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| Criteria aggregation model | |
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| Model development process | |
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| General framework | |
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| Mathematical formulation | |
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| Model development issues | |
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| The piece-wise linear modeling of marginal utilities | |
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| Uniqueness of solutions | |
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| The multi-group hierarchical discrimination method (MHDIS) | |
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| Outline and main characteristics | |
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| The hierarchical discrimination process | |
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| Estimation of utility functions | |
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| Model extrapolation | |
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| Post optimality techniques for classification model development in the UTADIS method | |
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| Experimental Comparison of Classification Techniques | |
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| Objectives | |
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| The considered methods | |
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| Experimental design | |
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| The factors | |
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| Data generation procedure | |
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| Analysis of results | |
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| Summary of major findings | |
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| Development of ELECTRE TRI classification models using a preference disaggregation approach | |
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| Classification Problems in Finance | |
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| Introduction | |
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| Bankruptcy prediction | |
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| Problem domain | |
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| Data and methodology | |
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| The developed models | |
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| The model of the UTADIS method | |
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| The model of the MHDIS method | |
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| The ELECTRE TRI model | |
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| The rough set model | |
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| The statistical models | |
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| Comparison of the bankruptcy prediction models | |
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| Corporate credit risk assessment | |
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| Problem domain | |
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| Data and methodology | |
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| The developed models | |
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| The UTADIS model | |
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| The model of the MHDIS method | |
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| The ELECTRE TRI model | |
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| The rough set model | |
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| The models of the statistical techniques | |
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| Comparison of the credit risk assessment models | |
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| Stock evaluation | |
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| Problem domain | |
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| Data and methodology | |
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| The developed models | |
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| The MCDA models | |
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| The rough set model | |
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| Comparison of the stock evaluation models | |
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| Conclusions and Future Perspectives | |
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| Summary of main findings | |
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| Issues for future research | |
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| References | |
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| Subject Index | |