Customer Churn with KNIME

This example is located in the EXAMPLES folder and the data is included. There are two data files, the Contract data and the CallData file. The video below walks through building the following workflow:

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Credit Scoring with KNIME

This workflow can be found on the KNIME EXAMPLES Server under 50_Applications/02_Credit_Scoring/01_CreditScoring.

This KNIME workflow focuses on creating 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.

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This workflow manipulates the data so it is suitable for a variety of modeling techniques by converting nominals to numerics. The data was enhanced so that understandable labels are used. It uses metanodes to “package” each technique suitable for reuse. Each Model uses a Test / Learn and cross validated process to ensure accuracy. The workflow writes out the model in the official PMML format, so that other applications can use the model.

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The data is German Credit data provided by

Professor Dr. Hans Hofmann

Institut für Statistik und Ökonometrie

Universität Hamburg

FB Wirtschaftswissenschaften

Von-Melle-Park 5 2000 Hamburg 13

Available at http://archive.ics.uci.edu/ml/datasets/Statlog+%28German+Credit+Data%29