omikuji
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tomtung
An efficient implementation of Partitioned Label Trees & its variations for extreme multi-label classification
Hey @tomtung! Do you think it would be possible to predefine tree architecture for parabel? It could be useful when labels are hierarchical by definition. Do you have any hints...
Sir, could you implement other performance measures? kindly share me code for the recall, nDCG in rust.
Hey @tomtung, great repository! Your implementation of parabel has significantly outperformed several architectures of DNN that I tried (for dataset of 600k samples, 20k labels) while being much faster at...
Bumps [zerocopy](https://github.com/google/zerocopy) from 0.7.20 to 0.7.31. Release notes Sourced from zerocopy's releases. v0.7.30 What's Changed [policies] Document yanking policy by @joshlf in google/zerocopy#677 [ci] Roll pinned nightly toolchain by @google-pr-creation-bot...
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Bumps [zerocopy](https://github.com/google/zerocopy) from 0.7.20 to 0.7.31. Release notes Sourced from zerocopy's releases. v0.7.30 What's Changed [policies] Document yanking policy by @joshlf in google/zerocopy#677 [ci] Roll pinned nightly toolchain by @google-pr-creation-bot...
I've adapted an alternative method to train the omikuji model by bypassing disk write for the Python wrapper. The main work is based on the creation of a new methods...
First of all, what a great library is this! Really congrats! I am using it on a classification problem with the python wrapper, as I wrote a small scikit-learn wrapper...
I was trying to load the `eurlex_train.txt` and `eurlex_test.txt`. As far as I understood they are in the LibSVM format for multilabel classification. Using the `sklearn.datasets.load_svmlight_file` fails though. I've observed...