Deployment
As discussed earlier, MLlib supports model export to Predictive Model Markup Language (PMML). Therefore, we do export some developed models to PMML for this project. However, in practice, the users for this project are more interested in rule-based decision making to use some of our insights besides score-based decision making to prevent frauds.
As for this project, the client is interested in applying our results for the following:
Deciding what interventions to use for a combination of car products or services with a special customer segment
When the company needs to start some interventions depending on the customer churn score
Therefore, we need to produce a customer churn risk score for the client with which the client will start some intervention when the score is above a cutting value. At the same time, we need to use the results from our logistic regression to recommend interventions.
Note
For more on exporting results from MLlib to PMML, please go to https://spark.apache.org...
