Data Mining and Analysis

Fundamental Concepts and Algorithms

Nonfiction, Computers, Database Management, General Computing
Cover of the book Data Mining and Analysis by Mohammed J. Zaki, Wagner Meira, Jr, Cambridge University Press
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Author: Mohammed J. Zaki, Wagner Meira, Jr ISBN: 9781107779105
Publisher: Cambridge University Press Publication: May 12, 2014
Imprint: Cambridge University Press Language: English
Author: Mohammed J. Zaki, Wagner Meira, Jr
ISBN: 9781107779105
Publisher: Cambridge University Press
Publication: May 12, 2014
Imprint: Cambridge University Press
Language: English

The fundamental algorithms in data mining and analysis form the basis for the emerging field of data science, which includes automated methods to analyze patterns and models for all kinds of data, with applications ranging from scientific discovery to business intelligence and analytics. This textbook for senior undergraduate and graduate data mining courses provides a broad yet in-depth overview of data mining, integrating related concepts from machine learning and statistics. The main parts of the book include exploratory data analysis, pattern mining, clustering, and classification. The book lays the basic foundations of these tasks, and also covers cutting-edge topics such as kernel methods, high-dimensional data analysis, and complex graphs and networks. With its comprehensive coverage, algorithmic perspective, and wealth of examples, this book offers solid guidance in data mining for students, researchers, and practitioners alike.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

The fundamental algorithms in data mining and analysis form the basis for the emerging field of data science, which includes automated methods to analyze patterns and models for all kinds of data, with applications ranging from scientific discovery to business intelligence and analytics. This textbook for senior undergraduate and graduate data mining courses provides a broad yet in-depth overview of data mining, integrating related concepts from machine learning and statistics. The main parts of the book include exploratory data analysis, pattern mining, clustering, and classification. The book lays the basic foundations of these tasks, and also covers cutting-edge topics such as kernel methods, high-dimensional data analysis, and complex graphs and networks. With its comprehensive coverage, algorithmic perspective, and wealth of examples, this book offers solid guidance in data mining for students, researchers, and practitioners alike.

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