I've the following dataset (just a example):
There exists any algorithm available that allows me to predictive Consumer Behavior like this: "When a customer buy a Jeans it also buys Food together"
The algorithms that I've found only calculate the most common products...not the association between them :( Anyone knows a good tutorial that shows me how can I predict the association that I said above?
The first step is to conclude this relationships:
Anyone have an Idea?Many thanks!!!
It sounds like you're looking for collaborative filtering, which does exist in spark.mllib: http://spark.apache.org/docs/1.6.2/mllib-collaborative-filtering.html
Amazon.com published a paper in 2003: "Amazon.com Recommendations: Item-to-Item Collaborative Filtering" which describes the algorithm in more detail. Quoting from the paper:
"the algorithm finds items similar to each of the user’s purchases and ratings, aggregates those items, and then recommends the most popular or correlated items".
Alex Woolford many thanks for your help :) In your case how can plan this project as a machine learning project? What I'm seeing is that the algorithms that I've been seen only count the occurrences. Thanks!