Introductory textbook presenting relational methods in machine learning.
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M. E. Mueller is a Professor of Computer Science at the Bonn-Rhein-Sieg University of Applied Sciences.
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Versandziele, Kosten & DauerAnbieter: Bahamut Media, Reading, Vereinigtes Königreich
Hardcover. Zustand: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee. Artikel-Nr. 6545-9780521190213
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Hardcover. Zustand: Very Good. Relational Knowledge Discovery This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. . Artikel-Nr. 7719-9780521190213
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 278 | Sprache: Englisch | Produktart: Bücher. Artikel-Nr. 22625232/2
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Anbieter: Labyrinth Books, Princeton, NJ, USA
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Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - What is knowledge and how is it represented This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual properties of different approaches. Artikel-Nr. 9780521190213
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Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Hardcover. Zustand: Brand New. 271 pages. 10.00x7.00x0.50 inches. In Stock. Artikel-Nr. x-0521190215
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