Data Mining Using SAS Applications

George Fernandez

382 pages, parution le 23/01/2003

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Résumé

Covers fundamental concepts before moving on to practical applications
Provides user-friendly SAS macro-call files through a supporting Web site at http://www.ag.unr.edu/gf/dm.html which also contains tips, updates, datasets, and an e-mail support service
Contains step-by-step instructions for performing data mining on sample datasets
Includes guidelines for performing complete data analysis, including sampling, data exploration, violation checking, model validations, and options for report generationSold separately, a companion CD-ROM contains all of the datasets, macro call-files, and the actual SAS macro files used in the book. See ISBN number 1-58488-379-0, Data Mining Using SAS Applications CD-ROM.

Most books on data mining focus on principles and furnish few instructions on how to carry out a data mining project. Data Mining Using SAS Applications not only introduces the key concepts but also enables readers to understand and successfully apply data mining methods using powerful yet user-friendly SAS macro-call files. These methods stress the use of visualization to thoroughly study the structure of data and check the validity of statistical models fitted to data.

Learn how to convert PC databases to SAS data
Discover sampling techniques to create training and validation samples
Understand frequency data analysis for categorical data
Explore supervised and unsupervised learning
Master exploratory graphical techniques
Acquire model validation techniques in regression and classification

The text furnishes 13 easy-to-use SAS data mining macros designed to work with the standard SAS modules. No additional modules or previous experience in SAS programming is required. The author shows how to perform complete predictive modeling, including data exploration, model fitting, assumption checks, validation, and scoring new data, on SAS datasets in less than ten minutes!

Contents

Data Mining - A Gentle Introduction
Preparing Data for Data Mining
Exploratory Data analysis
Unsupervised Learning Methods
Supervised Learning Methods - Prediction
Supervised Learning Methods -Classification
Emerging Technologies in Data Mining
Appendix: Instruction for Using the SAS Macros

L'auteur - George Fernandez

University of Nevada, Reno, Nevada, USA

Caractéristiques techniques

	PAPIER
Éditeur(s)	Chapman and Hall / CRC
Auteur(s)	George Fernandez
Parution	23/01/2003
Nb. de pages	382
Format	16 x 24
Couverture	Relié
Poids	685g
Intérieur	Noir et Blanc
EAN13	9781584883456
ISBN13	978-1-58488-345-6