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目标提升:净分介绍-Targeting Uplift: An Introduction to Net Scores

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上传于 2020-03-06 0次下载 983次围观
文件编号:6824
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标题(title):Targeting Uplift: An Introduction to Net Scores
目标提升:净分介绍
作者(author):René Michel, Igor Schnakenburg, Tobias von Martens
出版社(publisher):Springer International Publishing
大小(size):11 MB (11668270 bytes)
格式(extension):pdf
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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.







Table of contents :
Front Matter ....Pages i-xxxii
Introduction (René Michel, Igor Schnakenburg, Tobias von Martens)....Pages 1-6
The Traditional Approach: Gross Scoring (René Michel, Igor Schnakenburg, Tobias von Martens)....Pages 7-43
Basic Net Scoring Methods: The Uplift Approach (René Michel, Igor Schnakenburg, Tobias von Martens)....Pages 45-99
Validation of Net Models: Measuring Stability and Discriminatory Power (René Michel, Igor Schnakenburg, Tobias von Martens)....Pages 101-120
Supplementary Methods for Variable Transformation and Selection (René Michel, Igor Schnakenburg, Tobias von Martens)....Pages 121-136
A Simulation Framework for the Validation of Research Hypotheses on Net Scoring (René Michel, Igor Schnakenburg, Tobias von Martens)....Pages 137-146
Software Implementations (René Michel, Igor Schnakenburg, Tobias von Martens)....Pages 147-189
Data Prerequisites (René Michel, Igor Schnakenburg, Tobias von Martens)....Pages 191-239
Practical Issues and Business Cases (René Michel, Igor Schnakenburg, Tobias von Martens)....Pages 241-319
Summary and Outlook (René Michel, Igor Schnakenburg, Tobias von Martens)....Pages 321-325
Back Matter ....Pages 327-351
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