| Prologue | p. xi |
| Introduction to the Classification Problem | |
| Decision making problematics | p. 1 |
| The classification problem | p. 4 |
| General outline of classification methods | p. 6 |
| The proposed methodological approach and the objectives of the book | p. 10 |
| Review of Classification Techniques | |
| Introduction | p. 15 |
| Statistical and econometric techniques | p. 15 |
| Discriminant analysis | p. 16 |
| Logit and probit analysis | p. 16 |
| Non-parametric techniques | p. 24 |
| Neural networks | p. 24 |
| Machine learning | p. 27 |
| Fuzzy set theory | p. 30 |
| Rough sets | p. 32 |
| Multicriteria Decision Aid Classification Techniques | |
| Introduction to multicriteria decision aid | p. 39 |
| Objectives and general framework | p. 39 |
| Brief historical review | p. 40 |
| Basic concepts | p. 41 |
| Methodological approaches | p. 43 |
| Multiobjective mathematical programming | p. 45 |
| Multiattribute utility theory | p. 48 |
| Outranking relation theory | p. 50 |
| Preference disaggregation analysis | p. 52 |
| MCDA techniques for classification problems | p. 55 |
| Techniques based on the direct interrogation of the decision maker | p. 55 |
| The AHP method | p. 55 |
| The ELECTRE TRI method | p. 59 |
| Other outranking classification methods | p. 64 |
| The preference disaggregation paradigm in classification problems | p. 66 |
| Preference Disaggregation Classification Methods | |
| Introduction | p. 77 |
| The UTADIS method | p. 78 |
| Criteria aggregation model | p. 78 |
| Model development process | p. 82 |
| General framework | p. 82 |
| Mathematical formulation | p. 86 |
| Model development issues | p. 96 |
| The piece-wise linear modeling of marginal utilities | p. 96 |
| Uniqueness of solutions | p. 97 |
| The multi-group hierarchical discrimination method (MHDIS) | p. 100 |
| Outline and main characteristics | p. 100 |
| The hierarchical discrimination process | p. 101 |
| Estimation of utility functions | p. 105 |
| Model extrapolation | p. 111 |
| Post optimality techniques for classification model development in the UTADIS method | p. 113 |
| Experimental Comparison of Classification Techniques | |
| Objectives | p. 123 |
| The considered methods | p. 124 |
| Experimental design | p. 126 |
| The factors | p. 126 |
| Data generation procedure | p. 131 |
| Analysis of results | p. 134 |
| Summary of major findings | p. 143 |
| Development of ELECTRE TRI classification models using a preference disaggregation approach | p. 150 |
| Classification Problems in Finance | |
| Introduction | p. 159 |
| Bankruptcy prediction | p. 161 |
| Problem domain | p. 161 |
| Data and methodology | p. 164 |
| The developed models | p. 172 |
| The model of the UTADIS method | p. 172 |
| The model of the MHDIS method | p. 174 |
| The ELECTRE TRI model | p. 176 |
| The rough set model | p. 178 |
| The statistical models | p. 179 |
| Comparison of the bankruptcy prediction models | p. 181 |
| Corporate credit risk assessment | p. 185 |
| Problem domain | p. 185 |
| Data and methodology | p. 188 |
| The developed models | p. 194 |
| The UTADIS model | p. 194 |
| The model of the MHDIS method | p. 196 |
| The ELECTRE TRI model | p. 199 |
| The rough set model | p. 200 |
| The models of the statistical techniques | p. 201 |
| Comparison of the credit risk assessment models | p. 202 |
| Stock evaluation | p. 205 |
| Problem domain | p. 205 |
| Data and methodology | p. 209 |
| The developed models | p. 215 |
| The MCDA models | p. 215 |
| The rough set model | p. 220 |
| Comparison of the stock evaluation models | p. 222 |
| Conclusions and Future Perspectives | |
| Summary of main findings | p. 225 |
| Issues for future research | p. 229 |
| References | p. 233 |
| Subject Index | p. 251 |
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