This workflow shows the deployment of using a Distribution Method. We read in pre-trained normalization PMML model and test data and apply the model to filter out distribution tails as potential outliers. It labels these outliers and will use a Case Switch to decide whether we notify if there is a fraudulent transaction or not.
This workflow demonstrates how we can use the Distribution Method on new data by performing the following steps:
1. Read the model and new data
2. Deploy the Normalization PMML Model on the new transaction
3. Mark Outliers
To use this workflow in KNIME, download it from the below URL and open it in KNIME:
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