The Leading eBooks Store Online
for Kindle Fire, Apple, Android, Nook, Kobo, PC, Mac, Sony Reader...
Data Mining
Practical Machine Learning Tools and Techniques, Second Edition
US$ 71.95
(+ tax)
Preview (read now)
Add to my own site
Give this ebook to a friend
Add to my wishlist
Author's page
Publisher's page
Devices
- iPhone / iPad
- Android phones & tablets
- Kindle Fire
- e-readers with Adobe Digital Editions installed
- PC
- Mac
See the full list
Available Devices
X
This book is available for the following devices:
- iPhone
- iPad
- Android
- Kindle Fire
- Windows
- Mac
- Sony Reader
- Cool-er Reader
- Nook
- Kobo Reader
- iRiver Story
File Formats
Download: EPUB or secure PDF.
You can also read this book online in eb20 format without having to download anything.
You can also read this book online in eb20 format without having to download anything.
Permissions
Printing
Copy/Paste
Read Aloud
Printing
Copy/Paste
Read Aloud
more
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 less
Elsevier Science; July 2005
560 pages; ISBN 9780080477022
Read online, or download in EPUB or secure PDF format
560 pages; ISBN 9780080477022
Read online, or download in EPUB or secure PDF format
Subject categories
- Academic > Mathematics > General > Mathematics
- Academic > Computer Science > Computer science
- Academic > Computer Science > Electronic data processing
- Academic > Computer Science > Computers - special aspects
- Academic > Computer Science > System design; Periodicals
- Academic > Computer Science > Database management
- Academic > Computer Science > Data mining
- Academic > Mathematics > Instruments and machines
- Academic > Mathematics > Geometry. Trigonometry.Topology
- Computers > Database Management > Data Mining
- Computers > Information Storage & Retrieval
- Computers > Artificial Intelligence
ISBNs
008047702X
9780080477022
9780120884070

