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For the upcoming RFM Segmentation Notebook, I want to compare clv.utils.rfm_segments against more sophisticated (albeit computationally intensive) clustering methods.
I'm envisioning a Dirichlet process for estimating the number of segments:
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For the upcoming RFM Segmentation Notebook, I want to compare
clv.utils.rfm_segments
against more sophisticated (albeit computationally intensive) clustering methods.I'm envisioning a Dirichlet process for estimating the number of segments:
And/or a Gaussian Mixture Model to identify "fringe" customers for conversion:
These could be great additions to the library!
(Images taken from the linked notebooks in the
pymc
docs)Beta Was this translation helpful? Give feedback.
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