HomeGroupsTalkZeitgeist
Hide this

Results from Google Books

Click on a thumbnail to go to Google Books.

Data Mining: Practical Machine Learning…
Loading...

Data Mining: Practical Machine Learning Tools and Techniques

by Ian H. Witten

MembersReviewsPopularityAverage ratingConversations
299None37,269 (3.74)None
None

None.

Loading...

Sign up for LibraryThing to find out whether you'll like this book.

No current Talk conversations about this book.

No reviews
no reviews | add a review
You must log in to edit Common Knowledge data.
For more help see the Common Knowledge help page.
Series (with order)
Canonical title
Original title
Alternative titles
Original publication date
People/Characters
Important places
Important events
Related movies
Awards and honors
Epigraph
Dedication
First words
Quotations
Last words
Disambiguation notice
Publisher's editors
Blurbers
Publisher series

References to this work on external resources.

Wikipedia in English (3)

Book description
Haiku summary

Amazon.com Product Description (ISBN 0120884070, Paperback)

As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data. But there is no magic in machine learning, no hidden power, no alchemy. Instead there is an identifiable body of practical techniques that can extract useful information from raw data. This book describes these techniques and shows how they work.

The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references. The highlights for the new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive interface; comprehensive information on neural networks; a new section on Bayesian networks; plus much more.

* Algorithmic methods at the heart of successful data mining-including tried and true techniques as well as leading edge methods
* Performance improvement techniques that work by transforming the input or output
* Downloadable Weka, a collection of machine learning algorithms for data mining tasks, including tools for data pre-processing, classification, regression, clustering, association rules, and visualization-in a new, interactive interface

(retrieved from Amazon Mon, 30 Sep 2013 13:49:26 -0400)

(see all 2 descriptions)

No library descriptions found.

Quick Links

Swap Ebooks Audio
21 wanted4 pay

Popular covers

Rating

Average: (3.74)
0.5
1
1.5 1
2
2.5 1
3 7
3.5 2
4 8
4.5 1
5 5

Is this you?

Become a LibraryThing Author.

 

Help/FAQs | About | Privacy/Terms | Blog | Contact | LibraryThing.com | APIs | WikiThing | Common Knowledge | Legacy Libraries | Early Reviewers | 89,599,733 books! | Top bar: Always visible