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Data Mining

Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations.

This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.

This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.

Data Mining: Practical Machine Learning Tools and Techniques (The Morgan Kaufmann Series in Data Management Systems) 3rd Edition

'...offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations.'

I strongly recommend this book to all newcomers to data mining, especially to those who wish to understand the fundamentals of machine learning algorithms.'--INFORMS Journal of Computing 'The third edition of this practical guide to machine learning and data mining is fully updated to account for technological advances since its previous printing in 2005 and is now even more closely aligned with the use of the Weka open source machine learning, data mining and data modeling application.

Beginning with an introduction to data mining, the volume explores basic inputs, outputs and algorithms, the implementation of machine learning schemes and in-depth exploration of the many uses of the Weka data analysis software.

Witten, Frank and Hall are academics with the department of computer science at the University of Waikato, New Zealand, the home of the Weka software project.'--Book News, Reference & Research 'I would recommend this book to anyone who is getting started in either data mining or machine learning and wants to learn how the fundamental algorithms work.

I strongly recommend this book to all newcomers to data mining, especially to those who wish to understand the fundamentals of machine learning algorithms.'--INFORMS Journal of Computing 'The third edition of this practical guide to machine learning and data mining is fully updated to account for technological advances since its previous printing in 2005 and is now even more closely aligned with the use of the Weka open source machine learning, data mining and data modeling application.

Witten, Frank and Hall are academics with the department of computer science at the University of Waikato, New Zealand, the home of the Weka software project.'--Book News, Reference & Research 'I would recommend this book to anyone who is getting started in either data mining or machine learning and wants to learn how the fundamental algorithms work.

Data Mining: Practical Machine Learning Tools and Techniques, 3rd Edition

Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations.

The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals.