Principles of Data Mining explains and explores the principal techniques of Data Mining: for classification, association rule mining and clustering. Each topic is clearly explained and illustrated by detailed worked examples, with a focus on algorithms rather than mathematical formalism

Principles of Data Mining explains and explores the principal techniques of Data Mining: for classification, association rule mining and clustering. Each topic is clearly explained and illustrated by detailed worked examples, with a focus on algorithms rather than mathematical formalism. It is written for readers without a strong background in mathematics or statistics, and any formulae used are explained in detail

Undergraduate Topics in Computer Science. Principles of Data Mining. Artificial Intelligence in Theory and Practice.

Undergraduate Topics in Computer Science. Presents the principal techniques of data mining with particular emphasis on explaining and motivating the techniques used. Focuses on understanding of the basic algorithms and awareness of their strengths and weaknesses. Does not require a strong mathematical or statistical background. Artificial Intelligence: an International Perspective. Logic Programming with Prolog.

Max Bramer explains and explores the principal techniques of data mining, for classification, generation of association rules and clustering. ISBN13:9781846287657. Release Date:April 2007.

Principles of Data Mining. Book · January 2007 with 5,093 Reads. How we measure 'reads'. Undergraduate Topics in Computer Science ISSN 1863-7310. Isbn: 978-1-84628-765-7. cole Polytechnique, France and King’s College London, UK. Library of Congress Control Number: 2007922358. Digital Professor of Information Technology, University of Portsmouth, UK. Contents. Introduction to Data Mining.

Principles of Data Mining Series Foreword Preface Chapter 1. .

Published March 28, 2007 by Springer. Information storage and retrieval systems, Computer science, Artificial intelligence, Database management, Data mining.

Principles of Data Mining explains and explores the principal techniques of Data Mining: for classification, association rule mining and clustering. Published in Undergraduate Topics in Computer Science 2007. It is written for readers without a strong background in mathematics or statistics, and any formulae used are explained in detail.

This book explains the principal techniques of data mining: for classification, generation of association rules and clustering

This book explains the principal techniques of data mining: for classification, generation of association rules and clustering. It is written for readers without a strong background in mathematics or statistics and focuses on detailed examples and explanations of the algorithms given. Software Architecture in Action. Oquendo, . Leite, . Batista, T. (2016). This book presents a systematic model-based approach for software architecture according to three complementary viewpoints: structure, behavior, and execution.

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