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Data Mining Methods and Models

Wiley, J,
E-Book ( PDF mit Adobe DRM )
In Ihrem Land nicht verfügbar


Apply powerful Data Mining Methods and Models to Leverage your Datafor Actionable Results
Data Mining Methods and Models provides:
* The latest techniques for uncovering hidden nuggets ofinformation
* The insight into how the data mining algorithms actuallywork
* The hands-on experience of performing data mining on large datasets
Data Mining Methods and Models:
* Applies a "white box" methodology, emphasizing an understandingof the model structures underlying the softwareWalks the readerthrough the various algorithms and provides examples of theoperation of the algorithms on actual large data sets, including adetailed case study, "Modeling Response to Direct-MailMarketing"
* Tests the reader's level of understanding of the concepts andmethodologies, with over 110 chapter exercises
* Demonstrates the Clementine data mining software suite, WEKA opensource data mining software, SPSS statistical software, and Minitabstatistical software
* Includes a companion Web site, www.dataminingconsultant.com,where the data sets used in the book may be downloaded, along witha comprehensive set of data mining resources. Faculty adopters ofthe book have access to an array of helpful resources, includingsolutions to all exercises, a PowerPoint(r) presentation of eachchapter, sample data mining course projects and accompanying datasets, and multiple-choice chapter quizzes.
With its emphasis on learning by doing, this is an excellenttextbook for students in business, computer science, andstatistics, as well as a problem-solving reference for dataanalysts and professionals in the field.
An Instructor's Manual presenting detailed solutions to all theproblems in the book is available onlne.


Titel: Data Mining Methods and Models
Autoren/Herausgeber: Daniel T. Larose
Ausgabe: 1. Auflage

ISBN/EAN: 9780471756477

Seitenzahl: 386
Produktform: E-Book
Sprache: Englisch

DANIEL T. LAROSE, PhD, received his PhD in statistics from the University of Connecticut. An associate professor of statistics at Central Connecticut State University, he developed and directs Data Mining@CCSU, the world's first online master of science program in data mining. He has also worked as a data mining consultant for Connecticut-area companies. He is the author of Discovering Knowledge in Data: An Introduction to Data Mining (Wiley), and is currently working on the third book of his three-volume set on data mining: Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage (with Zdravko Markov, PhD), scheduled to be published by Wiley in 2006.

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