This workflow creates a credit scoring model based on historical data. As with all data mining modeling activities, it is unclear in advance which analytic method is most suitable. This workflow therefore uses three different methods simultaneously – Decision Trees, Neural Networking and SVM – then automatically determines which model is most accurate and writes that model out for further use. As a preprocessing step, this workflow converts nominals to numerics so the data are suitable for a variety of modeling techniques. Each model comes from a Learn / Test process including cross validation to ensure model stability. The workflow writes out the best performing model in the official PMML format, so that other applications can use the model.
To use this workflow in KNIME, download it from the below URL and open it in KNIME:Download Workflow
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