Machine Learning EWSL-91 : European Working Session on Learning, Porto, Portugal, March 6 8, 1991 : proceedings
Guardat en:
| Autor principal: | |
|---|---|
| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Col·lecció: | Lecture notes in computer science. Lecture notes in artificial intelligence
482 |
| Matèries: | |
| Accés en línia: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Actes d'un séminaire tenu à Porto du 6 au 8 mars 1991, d'après l écran-titre Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Machine learning, EWSL-91, proceedings, European Working Session on Learning, Porto, Portugal, March 6-8, 1991, Berlin, Springer-Verlag, 1991, 1 vol. (XI-537 p.), Lecture notes in computer science, 3-540-53816-X • Machine Learning - EWSL-91, Texte imprimé, 9783662190463 |
Taula de continguts:
- Abstracting background knowledge for concept learning
- A multistrategy learning approach to domain modeling and knowledge acquisition
- Using plausible explanations to bias empirical generalization in weak theory domains
- The replication problem: A constructive induction approach
- Integrating an explanation-based learning mechanism into a general problem-solver
- Analytical negative generalization and empirical negative generalization are not cumulative: A case study
- Evaluating and changing representation in concept acquisition
- Application of empirical discovery in knowledge acquisition
- Using accuracy in scientific discovery
- KBG : A generator of knowledge bases
- On estimating probabilities in tree pruning
- Rule induction with CN2: Some recent improvements
- On changing continuous attributes into ordered discrete attributes
- A method for inductive cost optimization
- When does overfitting decrease prediction accuracy in induced decision trees and rule sets?
- Semi-naive bayesian classifier
- Description contrasting in incremental concept formation
- System FLORA: Learning from time-varying training sets
- Message-based bucket brigade: An algorithm for the apportionment of credit problem
- Acquiring object-knowledge for learning systems
- Learning nonrecursive definitions of relations with linus
- Extending explanation-based generalization by abstraction operators
- Static learning for an adaptative theorem prover
- Explanation-based generalization and constraint propagation with interval labels
- Learning by explanation of failures
- PANEL : Logic and learnability
- Panel on : Causality and learning
- Seed space and version space: Generalizing from approximations
- Integrating EBL with automatic text analysis
- Abduction for explanation-based learning
- Consistent term mappings, term partitions, and inverse resolution
- Learning by analogical replay in prodigy: First results
- Analogical reasoning for logic programming
- Case-based learning of strategicknowledge
- Learning in distributed systems and multi-agent environments
- Learning to relate terms in a multiple agent environment
- Extending learning to multiple agents: Issues and a model for multi-agent machine learning (MA-ML)
- Applications of machine learning: Notes from the panel members
- Evaluation of learning systems : An artificial data-based approach
- Shift of bias in learning from drug compounds: The fleming project
- Learning features by experimentation in chess
- Representation and induction of musical structures for computer assisted composition
- IPSA: Inductive protein structure analysis
- Four stances on knowledge acquisition and machine learning
- Programme of EWSL-91.