lightfm
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lyst
A Python implementation of LightFM, a hybrid recommendation algorithm.
Hi @maciejkula. First: **This library is amazing** Second: I would like to know how to add a user to the model. It's easy to add the user to the interaction...
I noticed a strange issue using the library with the sparse matrices format. If I use the same interaction matrix but as CSR while training, I get different results when...
Hi, I train my LightFM model with no features for both users and products (I create a pure interaction matrix) based on implicit interactions. I score my model using mean...
I'm having a hard time understanding how the model learns the users and items biases and I'd loooove to have some guidance! haha I do understand the fact that **the...
Hi, I have a question which I need to ask the community. I have built a recommendation engine using LightFM and I am only taking customer's last 20 interactions to...
As far as I know, lightfm is dealing with implicit interaction matrix, i.e., 0s and 1s. However it can also creates a weight matrix separately and get into the training....
I appreciate the example in hybrid model in showing the difference in AUC. https://github.com/lyst/lightfm/blob/master/examples/stackexchange/hybrid_crossvalidated.ipynb However, it would be very helpful if you could also show the difference in using user...
Hi there, first: **Many thanks for the awesome library!** I would like to ask if the following use case of "social recommendations" is possible with LightFM (in a more or...
Hello! I'm building a recommendation system, and I'm having a similar problem to Issue #320, and I can't seem to find what is wrong. Particularly, I trained my model twice:...
Hi, This is not a question for this particular codebase, but I am just wondering how you achieve this. Recently I notice that if you are doing a collaborative filtering...