| 书目名称 | Introduction to Learning Classifier Systems | | 编辑 | Ryan J. Urbanowicz,Will N. Browne | | 视频video | | | 概述 | Learning Classifier Systems (LCSs) are a powerful and well-established rule-based machine learning technique but they have yet to be widely adopted due to a steep learning curve, their rich nature, an | | 丛书名称 | SpringerBriefs in Intelligent Systems | | 图书封面 |  | | 描述 | .This accessible introduction shows the reader how to understand, implement, adapt, and apply Learning Classifier Systems (LCSs) to interesting and difficult problems. The text builds an understanding from basic ideas and concepts. The authors first explore learning through environment interaction, and then walk through the components of LCS that form this rule-based evolutionary algorithm. The applicability and adaptability of these methods is highlighted by providing descriptions of common methodological alternatives for different components that are suited to different types of problems from data mining to autonomous robotics. . .The authors have also paired exercises and a simple educational LCS (eLCS) algorithm (implemented in Python) with this book. It is suitable for courses or self-study by advanced undergraduate and postgraduate students in subjects such as Computer Science, Engineering, Bioinformatics, and Cybernetics, and by researchers, data analysts, andmachine learning practitioners.. | | 出版日期 | Book 2017 | | 关键词 | Learning Classifier System (LCS); Computational Intelligence; Machine Learning (ML); Genetics-Based Mac | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-662-55007-6 | | isbn_softcover | 978-3-662-55006-9 | | isbn_ebook | 978-3-662-55007-6Series ISSN 2196-548X Series E-ISSN 2196-5498 | | issn_series | 2196-548X | | copyright | The Author(s) 2017 |
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发表于 2025-3-21 18:55:55
