Data Mining and Knowledge Discovery via Logic-Based Methods : Theory, Algorithms, and Applications
The importance of having efficient and effective methods for data mining and knowledge discovery (DM) is rapidly growing. This is due to the wide use of fast and affordable computing power and data storage media and also the gathering of huge amounts of data in almost all aspects of human activity a...
Gardado en:
| Autor Principal: | |
|---|---|
| Formato: | Livre numérique |
| Idioma: | Anglais |
| Publicado: |
Boston, MA :
Springer US : Springer e-books
[20..].
Cham : Springer Nature |
| Series: | Springer Optimization and Its Applications
43 |
| Acceso en liña: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Data Mining and Knowledge Discovery via Logic-Based Methods, Texte imprimé, 9781441916297 |
Table des matières:
- Algorithmic Issues Inferring a Boolean Function from Positive and Negative Examples A Revised Branch-and-Bound Approach for Inferring a Boolean Function from Examples Some Fast Heuristics for Inferring a Boolean Function from Examples An Approach to Guided Learning of Boolean Functions An Incremental Learning Algorithm for Inferring Boolean Functions A Duality Relationship Between Boolean Functions in CNF and DNF Derivable from the Same Training Examples The Rejectability Graph of Two Sets of Examples Application Issues The Reliability Issue in Data Mining: The Case of Computer-Aided Breast Cancer Diagnosis Data Mining and Knowledge Discovery by Means of Monotone Boolean Functions Some Application Issues of Monotone Boolean Functions Mining of Association Rules Data Mining of Text Documents First Case Study: Predicting Muscle Fatigue from EMG Signals Second Case Study: Inference of Diagnostic Rules for Breast Cancer A Fuzzy Logic Approach to Attribute Formalization: Analysis of Lobulation for Breast Cancer Diagnosis Conclusions