Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.

  • Apple
  • Android
  • Windows Phone
  • Android

To get the free app, enter your mobile phone number.

Data Mining: The Textbook 2015th Edition

4.7 out of 5 stars 8 customer reviews
ISBN-13: 978-3319141411
ISBN-10: 3319141414
Why is ISBN important?
ISBN
This bar-code number lets you verify that you're getting exactly the right version or edition of a book. The 13-digit and 10-digit formats both work.
Scan an ISBN with your phone
Use the Amazon App to scan ISBNs and compare prices.
Trade in your item
Get a $28.12
Gift Card.
Have one to sell? Sell on Amazon
Buy new
$85.49
In Stock.
Ships from and sold by Amazon.com. Gift-wrap available.
List Price: $89.99 Save: $4.50 (5%)
27 New from $64.19
Free Shipping for Prime Members | Fast, FREE Shipping with Amazon Prime
Data Mining: The Textbook has been added to your Cart
More Buying Choices
27 New from $64.19 24 Used from $63.94
Free Two-Day Shipping for College Students with Prime Student Free%20Two-Day%20Shipping%20for%20College%20Students%20with%20Amazon%20Student


Save up to 87% on Textbook Rentals Rent Textbooks
$85.49 Free Shipping for Prime Members | Fast, FREE Shipping with Amazon Prime In Stock. Ships from and sold by Amazon.com. Gift-wrap available.
click to open popover

Frequently Bought Together

  • Data Mining: The Textbook
  • +
  • Data Mining and Analysis: Fundamental Concepts and Algorithms
  • +
  • Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
Total price: $179.62
Buy the selected items together

Special Offers and Product Promotions

Editorial Reviews

Review

About the Author

NO_CONTENT_IN_FEATURE

Product Details

  • Hardcover: 734 pages
  • Publisher: Springer; 2015 edition (April 14, 2015)
  • Language: English
  • ISBN-10: 3319141414
  • ISBN-13: 978-3319141411
  • Product Dimensions: 7 x 1.6 x 10 inches
  • Shipping Weight: 2.2 pounds (View shipping rates and policies)
  • Average Customer Review: 4.7 out of 5 stars  See all reviews (8 customer reviews)
  • Amazon Best Sellers Rank: #365,413 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

Format: Kindle Edition
Data mining was lacking a text book that introduces the wide spectrum of different problems. This book specifically addresses that gap with the right amount of mathematical handling. It does not hand wave the students and gives the necessary intuition for each algorithm or model in simple english, which is then followed by the detailed mathematical or algorithmic treatment. I found the discussions very insightful with detailed pseudocodes, algorithm descriptions, and pictorial examples. Sometimes, I find that in some books you tend to get lost in the math. In this book, he provides explanations for all the equations. I particularly enjoyed the discussions on SVD and PCA, which provide not only the details of these methods, and the derivation, but also the various applications (which I do not find in other similar books). In ensemble methods, he provides interesting insights as to why these methods work. Different methods have also been compared at various places. I am still going through some of the chapters in detail. The book is quite easy to understand and would work well either as a graduate or undergraduate textbook.
Comment 11 people found this helpful. Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback.
Sorry, we failed to record your vote. Please try again
Report abuse
Format: Hardcover Verified Purchase
This book is a great resource on data mining. In the past, I found that these types of books are written either from a "data mining" perspective, or from a "machine learning" perspective. Data mining books frequently omit many basic machine learning methods such as linear, kernel, or logistic regression. However, machine learning books do not address basic data mining methods like association rules or outlier detection. This book finally provides about as complete coverage as one can hope to get from a single book. Two chapters are devoted to outlier detection. A remarkable and unusual feature is that methods for specific data types are covered in individually dedicated chapters. Even topic models are discussed, which are absent from information retrieval books.
Comment 10 people found this helpful. Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback.
Sorry, we failed to record your vote. Please try again
Report abuse
Format: Kindle Edition Verified Purchase
This is an excellent book both in depth and breadth of
the topics covered. It gives descriptions, analyses, and insights
about the most popular algorithms on various topics, and it covers
many more areas than most books. The book is well integrated across
the broad diversity of topics that are covered, and connections between
methods and topics are pointed out throughout the book. I wouldn't
agree with an earlier review that the descriptions are short or
introductory. For most of the important topics, a lot of detail is
provided in terms of algorithm description and pseudo-code.
In some cases, interesting analyses are also provided. For instance,
in the case of frequent pattern mining algorithms,
not only are more algorithms discussed
than most of the other books, but a discussion of multiple choices
of data structures for the same algorithm is provided,
along with their relative trade-offs. The relationships among various
algorithms are also discussed. I have seen quite a
few textbooks on data mining, and I have not seen anything close to this
level of detail in any of the other books. Overall, my impression is
that the author has done an excellent job of calibrating detail level
to topic importance. Therefore, it can serve both as a textbook and
as a reference book. On the other hand, this is certainly
not an implementation or programming-centric book. The book is good at
teaching principles and concepts.
Comment 8 people found this helpful. Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback.
Sorry, we failed to record your vote. Please try again
Report abuse
Format: Hardcover
A very clearly written book. It gives a lot of detail but you never feel overwhelmed because of the simple way in which it is presented. It stays away from the trap of dry presentation. If you really want to know the "whys" of data mining in addition to the "hows", this is a great book!
Comment 3 people found this helpful. Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback.
Sorry, we failed to record your vote. Please try again
Report abuse

Set up an Amazon Giveaway

Data Mining: The Textbook
Amazon Giveaway allows you to run promotional giveaways in order to create buzz, reward your audience, and attract new followers and customers. Learn more about Amazon Giveaway
This item: Data Mining: The Textbook