LibRecommender
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massquantity
Versatile End-to-End Recommender System
kindly look into error File "data_info.py", line 390, in add_oov item_sparse_oov = self.sparse_oov[self.item_sparse_col.index] IndexError: index 3 is out of bounds for axis 0 with size 3 i have change the...
At the implementation of "Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding" in `algorithm/cesar.py`, I have encountered a bug due to initializers. Here, I am reporting it and suggesting a...
Computation of recall at evaluation/metric.py does not consider "k" value which is passed as an arg. Whereas at the same module computation of precision uses "k" value. I think, there...
By default, tensorflow 1.14 alloctates whole RAM in GPU/s even though they are not needed in run-time. For ranker task, in this library, if indexing lib that uses GPU (for...
In the "recommend_user" method of the "WideDeep" class, it uses "np.argpartition" and there are some other methods. I do not see any nearest neighbors library. (such as; Faiss, ScaNN) Why...
How can I train models in multiple GPUs on the same machine. Current generic tf solution for keras API is using `tf.distribute.MirroredStrategy()` like below: ``` strategy = tf.distribute.MirroredStrategy() with strategy.scope():...
When I pass keras callback on the fit method (during ranking task), it does not affect the training process. ```Pyhton callbacks = [ EarlyStopping( monitor='recall', patience=1, restore_best_weights=True ) ] ```...
Hi, For NCF, there are two points I want to ask: * Split train, test data, as I see in this [repo](https://github.com/microsoft/recommenders/blob/main/examples/02_model_hybrid/ncf_deep_dive.ipynb): they do split as follows: * For each...
When running the 'pure collaborative-filtering example' , it only works on the first run. When rerunning the code I get the error message 'ValueError: Variable bu_var already exists, disallowed. Did...
I am struggling to use the models. I have a custom dataset, that has high sparsity --> n_users: 9026, n_items: 37, data sparsity: 6.2205 % Every model I have tried...
