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How much support do you need for your Data Mining results?

When querying your SSAS mining model you may have noted the prediction function predictsupport which is supplied by most of the mining algorithms, for example for the decision tree. The mining algorithm does not only predict a certain variable and gives the prediction score but also tells us how many cases were used to base this decision on (case support). You might have the feeling that cases with a lower support are not that reliable compared to cases with a higher support. This post is about how to determine the needed support for a given model.

To make this theoretical topic a little bit more practical, let’s look at actual data. For this post I’m using the targeted mailing decision tree model (TM Decision Tree) of the Adventure Works SSAS sample database. While you can do the same process described here with a data mining query result, I’m looking at the model itself instead. In order to do so I run the following query on my SSAS database:



Tags: data mining


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