The Comparison of Decision Tree Based Insurance Churn Prediction between Spark ML and SPSS
We have deployed a big data platform for the insurance company. One can select the data they need from database, do data analysis job and save the final model to the model pool using the platform. We completed churn prediction task on both SPSS [1] and Spark [7] using the data providing by X insurance company and carefully compared the execution flow, runtime, model evaluation, and model precision of each. Experimental results confirm that Spark ML [6] is easy to use and can cope with big data problems.
2016 9th International Conference on Service Science (ICSS)