Question building binary recommender system
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- Python
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Description
Hello,
this question had been asked similar before but unfortunately did not answer my problem.
So firstly, the data has a unique user-id as a row and about 1000 columns (each for a product) filled with a 1 if the extra was chosen and 0 if not. Having a look at the documentation of LightFM, I found that the data can be implicit, however on the same page is written something about ratings from 1 -5 for the MovieLens dataset. If I understood everything correctly, there is not problem that my data is binary, is it?
Secondly, splitting the data into train and test, I do not completely understand what the model tests on the test set?
Thank you in advance and best regards,
Brk
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Research direction
Start with the LightFM documentation and the earlier similar question mentioned in the thread; compare the implicit-data, MovieLens, and train/test discussions. Done means the intended handling of binary interactions and what evaluation on the test set measures are explained clearly, with the relevant documentation location identified.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100