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  • MPI Ethno. Forsch.  (3)
  • 2005-2009  (3)
  • SAS Institute  (3)
  • Data mining  (2)
  • Computer programming  (1)
  • 1
    Online Resource
    Online Resource
    Cary, N.C. : SAS Institute
    ISBN: 9781599946498 , 1599946491
    Language: English
    Pages: 1 online resource (xiv, 446 p.) , ill.
    Parallel Title: Erscheint auch als
    Keywords: SAS (Computer file) ; SAS (Computer program language) ; Computer programming ; Engineering ; Statistical methods ; Application software ; Development ; Mathematical statistics ; Data processing ; Electronic books ; local
    Abstract: "Most of the material in this book is geared toward a general audience, engineers will especially benefit from the focus on analysis of quality and reliability data. This book was prepared using SAS 9.2 and the companion code to the book includes a set of commonly used utility macros that allows SAS users to wield maximum power with minimal effort."--Publishers description.
    Note: Description based on print version record. - Includes bibliographical references (p. [409]-417) and index
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    Cary, NC : SAS Pub.
    ISBN: 9781599946344 , 1599946343
    Language: English
    Pages: 1 online resource (1 v.) , ill.
    Series Statement: SAS Press series
    Parallel Title: Erscheint auch als
    Keywords: SAS (Computer file) ; Receiver operating characteristic curves ; Computer programs ; SAS (Computer program language) ; Data mining ; Diagnosis ; Data processing ; Medical statistics ; Computer programs ; Electronic books ; Electronic books ; local
    Abstract: As a diagnostic decision-making tool, receiver operating characteristic (ROC) curves provide a comprehensive and visually attractive way to summarize the accuracy of predictions. They are used extensively in medical diagnosis and increasingly in fields such as data mining, credit scoring, weather forecasting, and psychometry. In Analyzing Receiver Operating Characteristic Curves with SAS, author Mithat Gonen illustrates the many existing SAS procedures that can be tailored to produce ROC curves and expands upon further analyses using other SAS procedures and macros. Both parametric and nonparametric methods for analyzing ROC curves are covered in detail. Topics addressed include: Appropriate methods for binary, ordinal, and continuous measures Computations using PROC FREQ, PROC LOGISTIC, PROC NLMIXED, and macros Comparing the ROC curves of several markers and adjusting them for covariates ROC curves with censored data Using the ROC curve for evaluating multivariable prediction models via bootstrap and cross-validation ROC curves in SAS Enterprise Miner And more! Written for any statistician interested in learning more about ROC curve methodology, the book assumes readers have a basic understanding of regression procedures and moderate familiarity with Base SAS and SAS/STAT. Some familiarity with SAS/GRAPH is helpful but not essential. This book is part of the SAS Press program.
    Note: Includes bibliographical references and index. - Description based on print version record
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Online Resource
    Online Resource
    Cary, N.C. : SAS Institute | Boston, Mass. :Safari Books Online,
    ISBN: 9781599940472 , 1599940477
    Language: English
    Pages: xxii, 408 p , ill. , 28 cm
    Series Statement: SAS Press series
    Keywords: SAS (Computer file) ; Enterprise Miner ; Business ; Data processing ; Electronic data processing ; Commercial analysis ; Data marts ; Data mining ; Time-series analysis ; Electronic books ; local
    Abstract: Written for anyone involved in the data preparation process for analytics, Gerhard Svolba's Data Preparation for Analytics Using SAS offers practical advice in the form of SAS coding tips and tricks, and provides the reader with a conceptual background on data structures and considerations from a business point of view. The tasks addressed include viewing analytic data preparation in the context of its business environment, identifying the specifics of predictive modeling for data mart creation, understanding the concepts and considerations of data preparation for time series analysis, using various SAS procedures and SAS Enterprise Miner for scoring, creating meaningful derived variables for all data mart types, using powerful SAS macros to make changes among the various data mart structures, and more!
    Note: Includes index
    Library Location Call Number Volume/Issue/Year Availability
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