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Beschreibung
This book is proposing a hybrid algorithm of two fuzzy genetic-based machine learning approaches - Michigan and Pittsburgh - for designing fuzzy rule-based classification systems. The search ability of each approach is examined to efficiently find fuzzy rule-based systems with high classification accuracy. These two approaches are combined into a single hybrid algorithm. The generalization ability of fuzzy rule-based classification systems, designed by the proposed hybrid algorithm is examined on real data sets. Experimental results show that the hybrid algorithm has higher search ability within a population of individual rules and within a population of rule sets.
Details
| Verlag | LAP LAMBERT Academic Publishing |
| Ersterscheinung | 17. Mai 2016 |
| Maße | 22 cm x 15 cm x 0.9 cm |
| Gewicht | 227 Gramm |
| Format | Softcover |
| ISBN-13 | 9783659891038 |
| Seiten | 140 |
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