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Targeting uplift = an introduction t...

Michel, Rene.

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Targeting uplift = an introduction to net scores /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Targeting uplift/ by Rene Michel, Igor Schnakenburg, Tobias von Martens.
Reminder of title:	an introduction to net scores /
Author:	Michel, Rene.
other author:	Schnakenburg, Igor.
Published:	Cham :Springer International Publishing : : 2019.,
Description:	xxxii, 352 p. :ill., digital ;24 cm.
[NT 15003449]:	List of Symbols -- List of Figures -- List of Tables -- Introduction -- The Traditional Approach: Gross Scoring -- Basic Net Scoring Methods: The Uplift Approach -- Validation of Net Models: Measuring Stability and Discriminatory Power -- Supplementary Methods for Variable Transformation and Selection -- A Simulation Framework for the Validation of Research Hypotheses on Net Scoring -- Software Implementations -- Data Prerequisites -- Practical Issues and Business Cases -- Summary and Outlook -- Appendix -- Other Literature on Net Scoring -- Index.
Contained By:	Springer eBooks
Subject:	Data mining. -
Online resource:	https://doi.org/10.1007/978-3-030-22625-1
ISBN:	9783030226251

Targeting uplift = an introduction to net scores /
Michel, Rene.

Targeting upliftan introduction to net scores /[electronic resource] :by Rene Michel, Igor Schnakenburg, Tobias von Martens. - Cham :Springer International Publishing :2019. - xxxii, 352 p. :ill., digital ;24 cm.

List of Symbols -- List of Figures -- List of Tables -- Introduction -- The Traditional Approach: Gross Scoring -- Basic Net Scoring Methods: The Uplift Approach -- Validation of Net Models: Measuring Stability and Discriminatory Power -- Supplementary Methods for Variable Transformation and Selection -- A Simulation Framework for the Validation of Research Hypotheses on Net Scoring -- Software Implementations -- Data Prerequisites -- Practical Issues and Business Cases -- Summary and Outlook -- Appendix -- Other Literature on Net Scoring -- Index.

This book explores all relevant aspects of net scoring, also known as uplift modeling: a data mining approach used to analyze and predict the effects of a given treatment on a desired target variable for an individual observation. After discussing modern net score modeling methods, data preparation, and the assessment of uplift models, the book investigates software implementations and real-world scenarios. Focusing on the application of theoretical results and on practical issues of uplift modeling, it also includes a dedicated chapter on software solutions in SAS, R, Spectrum Miner, and KNIME, which compares the respective tools. This book also presents the applications of net scoring in various contexts, e.g. medical treatment, with a special emphasis on direct marketing and corresponding business cases. The target audience primarily includes data scientists, especially researchers and practitioners in predictive modeling and scoring, mainly, but not exclusively, in the marketing context.

ISBN: 9783030226251

Standard No.: 10.1007/978-3-030-22625-1doiSubjects--Topical Terms:

562972
Data mining.

LC Class. No.: QA76.9.D343 / M534 2019

Dewey Class. No.: 006.312

Targeting uplift = an introduction to net scores /
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100 1 $a Michel, Rene. $3 3414406
245 1 0 $a Targeting uplift $h [electronic resource] : $b an introduction to net scores / $c by Rene Michel, Igor Schnakenburg, Tobias von Martens.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xxxii, 352 p. : $b ill., digital ; $c 24 cm.
505 0 $a List of Symbols -- List of Figures -- List of Tables -- Introduction -- The Traditional Approach: Gross Scoring -- Basic Net Scoring Methods: The Uplift Approach -- Validation of Net Models: Measuring Stability and Discriminatory Power -- Supplementary Methods for Variable Transformation and Selection -- A Simulation Framework for the Validation of Research Hypotheses on Net Scoring -- Software Implementations -- Data Prerequisites -- Practical Issues and Business Cases -- Summary and Outlook -- Appendix -- Other Literature on Net Scoring -- Index.
520 $a This book explores all relevant aspects of net scoring, also known as uplift modeling: a data mining approach used to analyze and predict the effects of a given treatment on a desired target variable for an individual observation. After discussing modern net score modeling methods, data preparation, and the assessment of uplift models, the book investigates software implementations and real-world scenarios. Focusing on the application of theoretical results and on practical issues of uplift modeling, it also includes a dedicated chapter on software solutions in SAS, R, Spectrum Miner, and KNIME, which compares the respective tools. This book also presents the applications of net scoring in various contexts, e.g. medical treatment, with a special emphasis on direct marketing and corresponding business cases. The target audience primarily includes data scientists, especially researchers and practitioners in predictive modeling and scoring, mainly, but not exclusively, in the marketing context.
650 0 $a Data mining. $3 562972
650 1 4 $a Statistics for Business, Management, Economics, Finance, Insurance. $3 3382132
650 2 4 $a Business Information Systems. $3 892640
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
650 2 4 $a Marketing. $3 536353
650 2 4 $a Statistical Theory and Methods. $3 891074
700 1 $a Schnakenburg, Igor. $3 3414407
700 1 $a von Martens, Tobias. $3 3414408
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856 4 0 $u https://doi.org/10.1007/978-3-030-22625-1
950 $a Mathematics and Statistics (Springer-11649)