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2016 | OriginalPaper | Chapter

9. Using R with the Modeler

Authors : Tilo Wendler, Sören Gröttrup

Published in: Data Mining with SPSS Modeler

Publisher: Springer International Publishing

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Abstract

The IBM SPSS Modeler provides a wide range of algorithms, procedures, and options to build statistical models. These options for creating models and preparing data are easy to understand and also intuitive. However, each statistical software package has its advantages, and the option to use R functionalities within the IBM SPSS Modeler as well gives the user the chance to lock on the same data from different angels and to use the best method provided by both software packages.
This chapter explains the most important steps in how to use R functionalities and to implement the correct code in the IBM SPSS Modeler. The procedure of how to install R and the IBM SPSS R Essentials is explained in detail. Furthermore, the R nodes of the Modeler that uses the R functionalities and present the results to the user are outlined.
After finishing this chapter, the reader is able to …
1.
Explain how to connect the IBM SPSS Modeler with R and why this can be helpful,
 
2.
Describe the advantages of implementing R features in a Modeler stream,
 
3.
Extending a stream by using the correct node to incorporate R procedures in a stream as well as
 
4.
Use R features to determine the best transformation of a variable towards normality.
 

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Literature
Metadata
Title
Using R with the Modeler
Authors
Tilo Wendler
Sören Gröttrup
Copyright Year
2016
DOI
https://doi.org/10.1007/978-3-319-28709-6_9

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