I have a dataset with 3.3M rows and 8k unique products. I wanted to apply apriori algorithm to find association rules and connections between products. Well, I did it before on a much smaller database with 50k rows and maybe 200 unique products.. Someone knows how can I do it effectively with larger scales of data? How can I still make it work for me maybe there are tricks to reduce the scale of the data but still get effective results. Any help would be amazing! Reach me out if you experienced with this algorithm.
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The trick is: Don't use Apriori.
Use LCM or the top-down version of FP-Growth.
You can find my implementations here:
command line programs: https://borgelt.net/fim.html (eclat with option -o gives LCM)
Python: https://borgelt.net/pyfim.html
R: https://borgelt.net/fim4r.html