Hi Ferrel, Thank you for your patience. I will compare cooccurrence with FP-Growth.
Thank you very much! Guo 2015-07-01 1:30 GMT+08:00 Pat Ferrel <[email protected]>: > Yes, that is one of the most common uses of fp-growth. > > Instead a better way to look at this might be using cooccurrence. If you > collect the items bought in every shopping cart, one row per cart and > boolean value for every item bought, then perform mahout’s > spark-itemsimilarity this will produce a matrix row keyed by items and rows > consisting of items most often bought with the key item. The Driver output > is sorted so the most common items are the first in the list. > > Then for a given shopping cart with items in it, you have a knn problem > where you want to find items that were bought with the same list in the > current shopping cart. This is done by indexing the output of > spark-itemsimilarity with a search engine and querying with the current > contents of the cart. > > This is exactly how we do recommendations for individuals but instead of > training with user-item interactions and querying with user history we are > training with shopping carts and querying with the current contents. > > See this reference and replace every reference to a user with some > shopping cart id: > http://mahout.apache.org/users/algorithms/recommender-overview.html > http://mahout.apache.org/users/algorithms/intro-cooccurrence-spark.html > > On Jun 30, 2015, at 12:36 AM, guo weizhan <[email protected]> wrote: > > We want FP-Growth to do the Market Basket Analysis, is there any other > algorithm we can use? > > Thanks, > Guo > > 2015-06-22 8:37 GMT+08:00 Pat Ferrel <[email protected]>: > > > What is your application? > > > > On Jun 17, 2015, at 7:06 AM, guo weizhan <[email protected]> wrote: > > > > Hi All, > > > > I found the FP-Growth was deprecated since 0.8, but we want this > algorithm > > to do the association analysis. Do I have to use the old version or Is > > there any other association analysis I can use in the lastest version? > > > > > > Thanks, > > Guo > > > > > >
