
IBM SPSS Modeler Cookbook
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In the data used for modeling, we frequently find attributes with a large number of different categorical values. A typical example is product codes, identifying a product purchased by a customer.
A data attribute with many different values can cause problems for data mining algorithms; complex data can make the algorithms run slowly, and may make it more difficult to find the patterns in the data, leading to less accurate models. A useful step in data preparation is to simplify this kind of complex data by grouping the values of a categorical variable into a smaller range of values, where the grouping has a relationship to the problem to be solved.
This recipe shows how to group product codes by their relation to a target response variable. It produces product groups, which are groupings of product codes, based on deciles of the response rates for each product code.
This recipe uses the following files:
Transactions_File.txt
Promotions_File...
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