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IBM SPSS Modeler Cookbook

You're reading from   IBM SPSS Modeler Cookbook If you've already had some experience with IBM SPSS Modeler this cookbook will help you delve deeper and exploit the incredible potential of this data mining workbench. The recipes come from some of the best brains in the business.

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Product type Paperback
Published in Oct 2013
Publisher Packt
ISBN-13 9781849685467
Length 382 pages
Edition 1st Edition
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Toc

Table of Contents (11) Chapters Close

Preface 1. Data Understanding FREE CHAPTER 2. Data Preparation – Select 3. Data Preparation – Clean 4. Data Preparation – Construct 5. Data Preparation – Integrate and Format 6. Selecting and Building a Model 7. Modeling – Assessment, Evaluation, Deployment, and Monitoring 8. CLEM Scripting A. Business Understanding Index

Imputing missing values randomly from uniform or normal distributions

Filling missing values with a random number is often preferable to filling with a constant, such as the mean or median. If the distribution of a variable matches or nearly matches a known distribution, such as a uniform or normal distribution, one can use the functions in Modeler to generate random numbers, given the parameters needed to generate the random numbers.

In this recipe we will impute missing values with random distributions: uniform and normal.

Getting ready

This recipe uses the following files:

  1. Datafile: cup98lrn_variable cleaning random impute recipe.sav
  2. Stream file: Recipe - impute random with known random distribution.str

How to do it...

To impute missing values randomly with uniform or normal distributions:

  1. Open the Recipe - impute random with known random distribution.str file by navigating to File | Open Stream.
  2. Make sure the datafile points to the correct path to the file cup98lrn_variable cleaning random impute...
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