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Book synopsis

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.

Book details

• Full title: Evolutionary Machine Learning in Linguistic Knowledge Extraction
• Author: Lamiaa Ahmed, Amr Badr, Mostafa Abd El-Azim
• Language: English
• Binding: Paperback
• Number of pages: 140
• EAN: 9783659891038
• ID: 13411736
• Publisher: LAP Lambert Academic Publishing
• Weight: 225 g
• Dimensions: 220 × 150 × 8 mm
• Published: 2016

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