Asia Pacific University Library catalogue


Predictive modeling with SAS enterprise miner : practical solutions for business applications / Kattamuri S. Sarma

By: Sarma, Kattamuri SMaterial type: TextTextPublication details: Cary, N.C. : SAS Institute, c2013Edition: 2nd edDescription: xxii, 478 p. : ill. ; 28 cmISBN: 9781607647676 (pbk.)Subject(s): Enterprise miner | SAS (Computer file) | Business -- Data processing | Data mining | Regression analysis -- Computer programs | Statistics -- Data processingGenre/Form: Electronic books LOC classification: HF5548.2 | .S27 2013
Contents:
Research strategy -- Getting started with predictive modeling -- Variable selection and transformation of variables -- Building decision tree models to predict response and risk -- Neural network models to predict response and risk -- Regression models -- Comparison and combination of different models -- Customer profitability -- Introduction to predictive modeling with textual data
    Average rating: 0.0 (0 votes)
Item type Current library Collection Call number Copy number Status Date due Barcode
General Circulation General Circulation APU Library
Open Shelf
Book HF5548.2 .S27 2013 c.1 (Browse shelf (Opens below)) 1 Available (No use restrictions) 00018066
General Circulation General Circulation APU Library
Open Shelf
Book HF5548.2 .S27 2013 c.2 (Browse shelf (Opens below)) 2 Available (No use restrictions) 00018067
Browsing APU Library shelves, Shelving location: Open Shelf, Collection: Book Close shelf browser (Hides shelf browser)
HF5548.2 .P67 1987 c.1 Up and running! : HF5548.2 .R69 2002 c.3 E-business : HF5548.2 .R69 2002 c.4 E-business : HF5548.2 .S27 2013 c.1 Predictive modeling with SAS enterprise miner : HF5548.2 .S27 2013 c.2 Predictive modeling with SAS enterprise miner : HF5548.2 .S46 1995 c.1 Information technology in business : HF5548.2 .S46 1998 c.1 Information technology in business :

Includes bibliographical references and index

Research strategy -- Getting started with predictive modeling -- Variable selection and transformation of variables -- Building decision tree models to predict response and risk -- Neural network models to predict response and risk -- Regression models -- Comparison and combination of different models -- Customer profitability -- Introduction to predictive modeling with textual data

There are no comments on this title.

to post a comment.