Maximum Relevance and Minimum Redundancy Feature Selection Methods for a Marketing Machine Learning Platform

15 Aug 2019Zhenyu ZhaoRadhika AnandMallory Wang

In machine learning applications for online product offerings and marketing strategies, there are often hundreds or thousands of features available to build such models. Feature selection is one essential method in such applications for multiple objectives: improving the prediction accuracy by eliminating irrelevant features, accelerating the model training and prediction speed, reducing the monitoring and maintenance workload for feature data pipeline, and providing better model interpretation and diagnosis capability... (read more)

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