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Titlebook: Genetic Programming Theory and Practice XIX; Leonardo Trujillo,Stephan M. Winkler,Wolfgang Banz Book 2023 The Editor(s) (if applicable) an

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發(fā)表于 2025-3-21 19:42:25 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Genetic Programming Theory and Practice XIX
編輯Leonardo Trujillo,Stephan M. Winkler,Wolfgang Banz
視頻videohttp://file.papertrans.cn/383/382610/382610.mp4
概述Provides a unique combination of theoretical contributions and state-of-the-art real-world problem.Explores the intersection of genetic programming and evolutionary computation in general.Discusses re
叢書(shū)名稱Genetic and Evolutionary Computation
圖書(shū)封面Titlebook: Genetic Programming Theory and Practice XIX; Leonardo Trujillo,Stephan M. Winkler,Wolfgang Banz Book 2023 The Editor(s) (if applicable) an
描述This book brings together some of the most impactful researchers in the field of Genetic Programming (GP), each one working on unique and interesting intersections of theoretical development and practical applications of this evolutionary-based machine learning paradigm. Topics of particular interest for this year′s book include powerful modeling techniques through GP-based symbolic regression, novel selection mechanisms that help guide the evolutionary process, modular approaches to GP, and applications in cybersecurity, biomedicine and program synthesis, as well as papers by practitioner of GP that focus on usability and real-world results. In summary, readers will get a glimpse of the current state of the art in GP research..
出版日期Book 2023
關(guān)鍵詞Genetic Programming; Genetic Programming Theory; Genetic Programming Applications; Symbolic Regression;
版次1
doihttps://doi.org/10.1007/978-981-19-8460-0
isbn_softcover978-981-19-8462-4
isbn_ebook978-981-19-8460-0Series ISSN 1932-0167 Series E-ISSN 1932-0175
issn_series 1932-0167
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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發(fā)表于 2025-3-21 21:08:55 | 只看該作者
Austausch von Daten zwischen Beteiligten, Employing correlation as a fitness function led to solutions being found in fewer generations compared to RMSE. We also found that fewer data points were needed in a training set to discover correct equations. The Feynman Symbolic Regression?Benchmark as well as several other old and recent GP benchmark problems were used to evaluate performance.
板凳
發(fā)表于 2025-3-22 03:17:42 | 只看該作者
Pseudonymes Audit in den Common Criteria,an be hard to create the right conditions to find good answers. To quote Shakespeare: “I can call the spirits from the vasty deep!” to which the response in the text is “Why so can I! And so can any [person], but will they come when you doth call?”
地板
發(fā)表于 2025-3-22 04:59:54 | 只看該作者
Correlation Versus RMSE Loss Functions in Symbolic Regression Tasks, Employing correlation as a fitness function led to solutions being found in fewer generations compared to RMSE. We also found that fewer data points were needed in a training set to discover correct equations. The Feynman Symbolic Regression?Benchmark as well as several other old and recent GP benchmark problems were used to evaluate performance.
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發(fā)表于 2025-3-22 11:40:49 | 只看該作者
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發(fā)表于 2025-3-22 14:45:01 | 只看該作者
Book 2023tionary process, modular approaches to GP, and applications in cybersecurity, biomedicine and program synthesis, as well as papers by practitioner of GP that focus on usability and real-world results. In summary, readers will get a glimpse of the current state of the art in GP research..
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發(fā)表于 2025-3-23 03:38:49 | 只看該作者
Rechte der betroffenen Personen, and explainable ML, and review research using GP for interpretability and explainability. We then introduce our previously proposed GP-based framework for interpretable and explainable learning applied to bioinformatics.
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發(fā)表于 2025-3-23 08:06:00 | 只看該作者
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