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02_​Deploying_​a_​Churn_​Predictor

Deploying a churn predictor

This workflow is an example of how to deploy a basic machine learning model (built in workflow "01_Training_a_Churn_Predictor") for churn prediction.

Notice the component "Churn Visualization" at the end of the workflow, which performs the visualization of (1) the input customers in a tile view and (2) the churning probabilities in a bar chart.

If you use this workflow, please cite:
F. Villaroel Ordenes & R. Silipo, “Machine learning for marketing on the KNIME Hub: The development of a live repository for marketing applications”, Journal of Business Research 137(1):393-410, DOI: 10.1016/j.jbusres.2021.08.036.

2. Here we apply the model over the newlyread data. 3. Below we produce ScoreCards and performvisualizations. 1. Below we read new data (contractdata and calls data) and the modelcreated in workflow"01_Training_a_Churn_Predictor". Churn Prediction: Deployment This workflow is an example of how to deploy a basic machine learning model (built in workflow "01_Training_a_Churn_Predictor") for churnprediction. Read new datatile view &bar chartpreparing forvisualizationFrom Random ForestPredictorApply model over new data CSV Reader Churn Visualization Data Prep Model Reader Random ForestPredictor 2. Here we apply the model over the newlyread data. 3. Below we produce ScoreCards and performvisualizations. 1. Below we read new data (contractdata and calls data) and the modelcreated in workflow"01_Training_a_Churn_Predictor". Churn Prediction: Deployment This workflow is an example of how to deploy a basic machine learning model (built in workflow "01_Training_a_Churn_Predictor") for churnprediction. Read new datatile view &bar chartpreparing forvisualizationFrom Random ForestPredictorApply model over new data CSV Reader Churn Visualization Data Prep Model Reader Random ForestPredictor

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