BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Data Mining : Practical Machine Learning Tools and Techniques

Data Mining : Practical Machine Learning Tools and Techniques

Data Mining : Practical Machine Learning Tools and Techniques Paperback - 2016 - 4th Edition

by Eibe Frank; Mark A. Hall; Christopher J. Palestro; Ian H. Witten

Add to wish list
  • Used
  • Good
  • Paperback
Used - Good

Description

Elsevier Science & Technology Books, 2016. Paperback. Good. Disclaimer:A copy that has been read, but remains in clean condition. All pages are intact, and the cover is intact. The spine may show signs of wear. Pages can include limited notes and highlighting, and the copy can include previous owner inscriptions. At ThriftBooks, our motto is: Read More, Spend Less.Dust jacket quality is not guaranteed.
Ask the seller a question Add to wish list
A$12.11
Free Delivery within USA
Standard delivery: 4 to 8 days
More delivery options
Ships from ThriftBooks (Washington, United States)
Biblio Top Seller
The BIBLIO Guarantee

Details

  • Title Data Mining : Practical Machine Learning Tools and Techniques
  • Author Eibe Frank; Mark A. Hall; Christopher J. Palestro; Ian H. Witten
  • Binding Paperback
  • Edition number 4th
  • Edition 4
  • Condition Used - Good
  • Pages 654
  • Volumes 1
  • Language ENG
  • Publisher Elsevier Science & Technology Books
  • Publication date 2016
  • Bookseller's Inventory # G0128042915I3N00
  • ISBN 9780128042915 / 0128042915
  • Weight 2.84 lbs (1.29 kg)
  • Dimensions 9.25 x 7.5 x 1.1 in (23.50 x 19.05 x 2.79 cm)
  • Category Computers - Data Base Management
  • Library of Congress subjects Data mining
  • Library of Congress Catalogue Number 2016948470
  • Quantity available 1

About ThriftBooks Washington, United States

Biblio member since 2018

From the largest selection of used titles, we put quality, affordable books into the hands of readers

Terms of Sale: 30 day return guarantee, with full refund including original shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

Browse books from ThriftBooks

Reader reviews for Data Mining : Practical Machine Learning Tools and Techniques

Write a review for this book

There are no reviews for this book yet. Be the first to write a review!

Your review will be anonymous unless you login or create an account first.

Overall rating
Remember: You’re rating the book as a work, not the seller or the condition of the specific copy you purchased!

Important Terms and Guidelines

  • Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
  • Reviews must be at least 140 characters in length.
  • Please do not reveal critical plot elements.
  • This is not a help line. Contact customer support if you need help.
Your review must not include:
  • Obscenities, discriminatory language, or other insulting language not suitable for public domain
  • Advertisements, “spam” content, or references to other products, offers or websites.
  • Email addresses, URLs, phone numbers, physical addresses or other contact information.
  • Overly critical comments about other reviews or reviewers
  • Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
  • Availability, price, or alternative ordering/shipping information

From the publisher

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.

Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.

Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.

It contains

  • Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
  • Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
  • Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.

Please wait a moment while we load the requested page.

tracking-