Hello All,
I have an input dataset (say approximately 1000 transactions having a total of 100,000 rows). I can use Association Rule Learner to analyze Support Confidence etc and decide upon important item sets. However is it possible to map those rule sets to those actual 1000 transactions anyhow through Knime?
Any help would be much appreciated please!
yes this is possible.
If you consider a association rule and want to apply this to a real transaction to predict. You need to find the best matching rule. Which is typically done by the one where the most antecedent items are included.
This can be done with the Subset Matcher node.
You can find an example here:
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