Applied Genetic Programming and Machine Learning - Hitoshi Iba - 書籍 - Taylor & Francis Ltd - 9780367385279 - 2019年10月10日
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Hitoshi Iba
Applied Genetic Programming and Machine Learning 第1 版

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What do financial data prediction, day-trading rule development, and bio-marker selection have in common? They are just a few of the tasks that could potentially be resolved with genetic programming and machine learning techniques. Written by leaders in this field, Applied Genetic Programming and Machine Learning delineates the extension of Genetic Programming (GP) for practical applications.





Reflecting rapidly developing concepts and emerging paradigms, this book outlines how to use machine learning techniques, make learning operators that efficiently sample a search space, navigate the search process through the design of objective fitness functions, and examine the search performance of the evolutionary system. It provides a methodology for integrating GP and machine learning techniques, establishing a robust evolutionary framework for addressing tasks from areas such as chaotic time-series prediction, system identification, financial forecasting, classification, and data mining.





The book provides a starting point for the research of extended GP frameworks with the integration of several machine learning schemes. Drawing on empirical studies taken from fields such as system identification, finanical engineering, and bio-informatics, it demonstrates how the proposed methodology can be useful in practical inductive problem solving.

349 pages

メディア 書籍     Paperback Book   (ソフトカバーで背表紙を接着した本)
リリース済み 2019年10月10日
ISBN13 9780367385279
出版社 Taylor & Francis Ltd
ページ数 349
寸法 365 × 156 × 21 mm   ·   596 g
言語 英語  

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