Ryan J. Urbanowicz, Will N. Browne

Introduction to Learning Classifier Systems (eBook, PDF)

• Format: PDF

Produktbeschreibung

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, and a lack of resources, and this is the first accessible introduction

Authors gave related tutorial at key international conference over multiple years

Suitable for undergraduate and postgraduate students, data analysts, and machine learning practitioners

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 123
• Erscheinungstermin: 17. August 2017
• Englisch
• ISBN-13: 9783662550076
• Artikelnr.: 53059935

Autorenporträt

Ryan Urbanowicz is a postdoctoral research associate in the Dept. of Biostatistics, Epidemiology, and Informatics in the Perelman School of Medicine at the University of Pennsylvania. He received his PhD in Genetics from Dartmouth College, and a B.S. and M.Eng. in Biological Engineering from Cornell University. His areas of research include bioinformatics, data mining, machine learning, evolutionary algorithms, learning classifier systems, data visualization, and epidemiology. He has cochaired the Intl. Workshop on Learning Classifier Systems and presented LCS tutorials at GECCO.

Will Browne is an Associate Professor in the School of Engineering and Computer Science of Victoria University of Wellington. He received his Eng.D. from Cardiff University. His main area of research is applied cognitive systems, in particular cognitive robotics, Learning Classifier Systems (LCSs), and modern heuristics for industrial application. He has cochaired the Intl. Workshop on Learning Classifier Systems, and chaired the Genetics-Based Machine Learning track and copresented the LCS tutorial at GECCO.

Inhaltsangabe

LCSs in a Nutshell.- LCS Concepts.- Functional Cycle Components.- LCS Adaptability.- Applying LCSs.

Rezensionen

"Introduction to Learning Classifier Systems is an excellent textbook and introduction to Learning Classifier Systems. ... The book is completed with Python code available through a link included in the book. ... Urbanowicz and Browne recommend their book for undergraduate and postgraduate students, data analysts, and machine learning practitioners alike." (Analía Amandi, Genetic Programming and Evolvable Machines, Vol. 19 (4), December, 2018)