implicit
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benfred
Fast Python Collaborative Filtering for Implicit Feedback Datasets
This PR resolves a few issues; - #412 "precision" on ranking_metrics_at_k is actually "recall" I guess it's fine to update precision and recall since this library took major braking update...
What happened to the evaluation code in the last version? Is evaluation not covered any more by this package? There is a discrepancy between the current version and the documentation....
```python ii_model = BM25Recommender(K=25, K1=1.5, B=1.) ii_model.fit(tr) ranking_metrics_at_k(ii_model, tr, te, K=100) ``` where tr has integral dtype. ``` ----> 2 ranking_metrics_at_k(ii_model, tr.astype(np.int32), te, K=100) File evaluation.pyx:436, in implicit.evaluation.ranking_metrics_at_k() File ~/miniforge3/lib/python3.9/site-packages/implicit/nearest_neighbours.py:54,...
I trained two ALS models for the same data on GPU and CPU, but for GPU, I have 0.06 for the loss, and in CPU, I have 0.0006 for loss....
The docs website could be added to GitHub repository details
I would like to tune hyper-parameters with implicit's `AlternatingLeastSquares`. Ideally, I would use cross-validation but it seems like there is no simple way to "fit" on training data and "predict"...
Hello, I'm facing a huge slowdown when fitting an ALS model in a docker container. The difference in speed is about x10. In both experiments I use the same settings...
Please tell me how it is possible to solve the cold start problem for users within the CosineRecomender model? Let's say I have a user whose interactions were not in...
It would be nice to have a popularity evaluation function to use as a baseline. I created one by modifying the ranking_metrics_at_k function by plugging in the K most popular....
I noticed something weird when I was using this function to split my data into train and test set I had a distribution of users and number of times they...
