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Data Mining - Practical Machine Learning Tools And Techniques With Java Implementations

by Eibe Frank, Ian H. Witten
Data Mining - Practical Machine Learning Tools And Techniques With Java Implementations - Thryft
Data Mining - Practical Machine Learning Tools And Techniques With Java Implementations - Thryft

Empower yourself with practical machine learning techniques.

This book is a must-have for anyone looking to gain a solid understanding of machine learning. With clear explanations and real-world examples, it offers practical advice on how to apply machine learning tools effectively. What sets it apart is the fully functional machine learning software that accompanies the book, giving readers a hands-on experience. Whether you're a beginner or already involved in data mining, this book will empower you to extract valuable knowledge from large datasets.

Note: While we do our best to ensure the accuracy of cover images, ISBNs may at times be reused for different editions of the same title which may hence appear as a different cover.

Data Mining - Practical Machine Learning Tools And Techniques With Java Implementations

by Eibe Frank, Ian H. Witten
Condition guide

Book Condition Guide

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This book may contain very minor cosmetic defects, but it is in pristine condition. There should be no yellowing, no foxing, no water damage, and no annotations of any kind on the cover and the pages. For paperbacks, there should not be any crease marks on the spine. This book is good as new — lucky you!

*Books may be missing bundle media (e.g. CD, e-book code), if included.

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This book has been used, but it is still in a clean condition. There should be no foxing or annotations of any kind on the inner pages, but a sparse amount may be present on the cover, title pages, or outside edges of the book. There should be no water damage of any kind. For paperbacks, there may be light crease marks on the spine.

*Books may be missing bundle media (e.g. CD, e-book code), if included.

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We do our best to ensure the quality of our books, but there is no escaping the wear and tear that comes with time. Slight foxing and some annotations may be present on the pages and the cover. There should be no water damage of any kind. For paperbacks, there may be several crease marks on the spine.

*Books may be missing bundle media (e.g. CD, e-book code), if included.

Books in Well Read Condition

This is a well-read book, which means that the previous owner probably really enjoyed it! The cover and pages may include moderate foxing and annotations, but the text is not obscured and still readable. Moderate cosmetic defects and minor water damage may be present on the edges of the book. For paperbacks, there may be multiple crease marks on the spine.

*Books may be missing bundle media (e.g. CD, e-book code), if included.

 

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ISBN: 9781558605527
Authors: Eibe Frank, Ian H. Witten
Publisher: Morgan Kaufmann
Date of Publication: 1999-10-25
Format: Paperback
Related Collections: Science
Related Topics: Computers
Goodreads rating: 3.9
(rated by 778 readers)

Description

This book 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. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining―including both tried-and-true techniques of the past and Java-based methods at the leading edge of contemporary research. If you're involved at any level in the work of extracting usable knowledge from large collections of data, this clearly written and effectively illustrated book will prove an invaluable resource. Complementing the authors' instruction is a fully functional platform-independent Java software system for machine learning, available for download. Apply it to the sample data sets provided to refine your data mining skills, apply it to your own data to discern meaningful patterns and generate valuable insights, adapt it for your specialized data mining applications, or use it to develop your own machine learning schemes. * Helps you select appropriate approaches to particular problems and to compare and evaluate the results of different techniques.* Covers performance improvement techniques, including input preprocessing and combining output from different methods.* Comes with downloadable machine learning use it to master the techniques covered inside, apply it to your own projects, and/or customize it to meet special needs.
 

Empower yourself with practical machine learning techniques.

This book is a must-have for anyone looking to gain a solid understanding of machine learning. With clear explanations and real-world examples, it offers practical advice on how to apply machine learning tools effectively. What sets it apart is the fully functional machine learning software that accompanies the book, giving readers a hands-on experience. Whether you're a beginner or already involved in data mining, this book will empower you to extract valuable knowledge from large datasets.

Note: While we do our best to ensure the accuracy of cover images, ISBNs may at times be reused for different editions of the same title which may hence appear as a different cover.