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Stream Mining for Churn Prediction by Kevin Mondragon is a document available to read on EtoBox.

What is Stream Mining for Churn Prediction about?

The document describes a system for predicting customer churn using stream mining methods. Stream mining allows detecting churn patterns in real-time data streams and adapting models quickly as customer behavior changes. The system is implemented using the MOA framework and Hoeffding trees to incrementally build models from streaming data. Preliminary results show the feasibility of high-throughput churn prediction on streaming customer data. However, further work is needed to scale the system to handle lar

Author

Kevin Mondragon

Language

EN