Research on the Application of Improved RFM Model and K-Means Algorithm in Membership Classification
Aiming at the distortion caused by traditional RFM models used for member classification,this paper proposes an improve-ment to the RFM model by adding two parameters:customer relationship length and customer purchase cycle.At the same time,a K-means algorithm based on sample object feature weighting and central initialization is proposed to address the prob-lems of traditional K-means algorithms.Using the improved RFM model for member classification can effectively improve classification efficiency.
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