Ahmet Erdem

@rohanrajpal RAPIDS cuML has NearestNeighbors implementation. It currently supports euclidean distance for dense matrices on GPU but they are working on cosine similarity on sparse matrices for future releases (probably...

Hi @AndreaPesce , thanks for your interest in this package. Default model has only simple checks and try to infer the most common use cases. You can provide your multi-class...

If the choice depends on the metric, then I have to keep a static list of all metrics, which will need to be updated every time sklearn is updated. Besides...

Good idea! I will work on it soon.

Thanks for your interest. Pre-trained embeddings would be basically for each Quora question, therefore I don't see a general use case for it. How do you plan to use them?...

Ah my bad, you didn't mean the sentence embeddings but the model weights. It is indeed possible. Nowadays, my GPU is busy with some Kaggle competitions. I can train a...

For your use case, non-NLP features (graph features) should be discarded. They were only helping for utilizing Kaggle's sampling bias: https://github.com/aerdem4/kaggle-quora-dup/blob/master/model.py#L149 Btw, I have noticed that my code needs serious...

Closing this because I never had time to do it. Please feel free to open a PR.