Evaluation and enhancement of Bayesian rule-sets in a genetic algorithm learning environment for classification tasks
| العنوان: | Evaluation and enhancement of Bayesian rule-sets in a genetic algorithm learning environment for classification tasks |
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| المؤلفون: | Ema Toto, Christoph F. Eick |
| المصدر: | Lecture Notes in Computer Science ISBN: 9783540584957 ISMIS |
| بيانات النشر: | Springer Berlin Heidelberg, 1994. |
| سنة النشر: | 1994 |
| مصطلحات موضوعية: | Learning classifier system, Wake-sleep algorithm, Computer science, business.industry, Population-based incremental learning, Bayesian probability, Stability (learning theory), Multi-task learning, Semi-supervised learning, Machine learning, computer.software_genre, Unsupervised learning, Artificial intelligence, business, computer |
| الوصف: | The paper describes a learning environment named DEL-VAUX for classification tasks that learns Bayesian rule-sets from sets of examples. A genetic algorithm approach is used for this purpose, in which a population consists of sets of rule-sets that generate offspring through the exchange of rules, permitting fitter rule-sets to produce offspring with a higher probability. A bucket brigade algorithm for Bayesian rule-sets called reward punishment mechanism is introduced, which evaluates the performance of a Bayesian rule within a rule-set. It employs fuzzy techniques to measure the ”goodness” of a rule within a rule-set. |
| ردمك: | 978-3-540-58495-7 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::a2bb56217964871165e3a5373c4e99a4 https://doi.org/10.1007/3-540-58495-1_37 |
| رقم الأكسشن: | edsair.doi...........a2bb56217964871165e3a5373c4e99a4 |
| قاعدة البيانات: | OpenAIRE |
| ردمك: | 9783540584957 |
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