Hi, New to mahout and fp growth. I havefollowed this example:https://chimpler.wordpress.com/2013/05/02/finding-association-rules-with-mahout-frequent-pattern-mining/ I generated nice output informationlike this (as an example): [abc,def,ghi] => klm,confidence:0.597, support:0.01, lift: 57.415, conviction: 2.453…...
Now I am not clear on how to model“recommendations” where given items [qrs, tuv] recommend wxy basedon confidence level. Am I to make lookups based on the above results or use one of the several recommender and similarity classesin mahout? A bit lost on where to start. Thanks
