I have a set of transactions that contain products and I am working on partitionning these products into clusters based on their affinity. In the literature, I found two measures for the product affinity. One is the support count and the other is the weighted support count. Which one should I use and when ?
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The R package arules
has an implementation to calculate affinity as defined by
Charu C. Aggarwal, Cecilia Procopiuc, and Philip S. Yu (2002) Finding localized associations in market basket data, IEEE Trans. on Knowledge and Data Engineering, 14(1):51-62.
Have a look at: https://www.rdocumentation.org/packages/arules/versions/1.6-1/topics/affinity

Michael Hahsler
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