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2019 | OriginalPaper | Buchkapitel

7. Software Implementations

verfasst von : René Michel, Igor Schnakenburg, Tobias von Martens

Erschienen in: Targeting Uplift

Verlag: Springer International Publishing

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Abstract

This chapter looks at different software implementations in order to mention which net scoring methods have been implemented in software packages and how those packages have to be handled. Different implementations, such as SAS, R, Pitney Bowes, and others, are presented and comments on their level of proficiency but also on their shortcomings are given. Remarks will be made with respect to the usability and the comfort offered by the different packages with regard to uplift model development, scoring, evaluation, deployment, and visualizations. For each presented software, some general comments on the provider and the package will be made. We detail the way that model preparation is supported, model building and scoring are handled, evaluation is implemented, and a roll-out may be automated. In the end, a comparative study will be presented where a net scoring model is built with each software on an identical dataset.

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Fußnoten
1
Current versions at the time of writing: SAS Foundation version 9.4, SAS Enterprise Guide version 7.1, SAS Enterprise Miner version 14.2.
 
2
While it is necessary to know the next steps in plain programming, using a selection menu may inspire the way of dealing with a given issue. At least, a menu will make alternatives obvious.
 
3
It is a recent trend to do programming and visualizations in the so-called note books, i.e., editors within the usual web browser (e.g., Jupyter or Zeppelin from the Apache framework). This has the advantage of easily being able to share codes and visualizations.
 
4
Ⓒ2016 Pitney Bowes Software Inc. All rights reserved. MapInfo and Group 1 Software are trademarks of Pitney Bowes Software Inc. All other marks and trademarks are property of their respective holders.
 
5
And into the authors’ SAS macro!
 
6
R can be freely downloaded from: https://​www.​r-project.​org/​.
 
7
On the same page (see previous footnote), manuals and introductions into R-programming can be freely downloaded as well. There are plenty of videos available on the web.
 
8
R Studio can be freely downloaded from: https://​www.​rstudio.​com/​.
 
9
This is not a feature of R random forests but random forests in general.
 
10
KNIME can be freely downloaded from: https://​www.​knime.​com/​.
 
11
Predictions here simply means scoring a dataset with an algorithm already found.
 
12
If business insights suggest a different way of proceeding, then this would have to be programmed by hand but may certainly be sensible.
 
13
Here, the general design of the tool is meant which allows drag-and-drop as well as programming. SAS Enterprise Miner offers uplift modeling only by means of graphics.
 
Literatur
2.
Zurück zum Zitat L. Guelman. Uplift modeling - an integrated package for building and testing uplift models. R Package Documentation, 2014. Version 0.3.5. L. Guelman. Uplift modeling - an integrated package for building and testing uplift models. R Package Documentation, 2014. Version 0.3.5.
3.
Zurück zum Zitat L. Guelman, M. Guillén, and A.M. Perez-Marin. Random forests for uplift modeling: an insurance customer retention case. Lecture Notes in Business Information Processing, (115):123–133, 2012.CrossRef L. Guelman, M. Guillén, and A.M. Perez-Marin. Random forests for uplift modeling: an insurance customer retention case. Lecture Notes in Business Information Processing, (115):123–133, 2012.CrossRef
4.
Zurück zum Zitat L. Guelman, M. Guillén, and A.M. Perez-Marin. Optimal personalized treatment rules for marketing interventions: A review of methods, a new proposal, and an insurance case study. UB Riskcenter Working Paper Series, 2014(06), 2014. L. Guelman, M. Guillén, and A.M. Perez-Marin. Optimal personalized treatment rules for marketing interventions: A review of methods, a new proposal, and an insurance case study. UB Riskcenter Working Paper Series, 2014(06), 2014.
5.
Zurück zum Zitat K. Larsen. Net Lift Models: Optimizing the Impact of Your Marketing Efforts - Course Notes. SAS Institute Inc., Cary, 2010. K. Larsen. Net Lift Models: Optimizing the Impact of Your Marketing Efforts - Course Notes. SAS Institute Inc., Cary, 2010.
Metadaten
Titel
Software Implementations
verfasst von
René Michel
Igor Schnakenburg
Tobias von Martens
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-22625-1_7