Sampling SVD singular vectors for Distributional Semantics Models
Project description
entropix
Generate count-based Distributional Semantic Models by sampling SVD singular vectors instead of using top components.
Install
pip install entropix
or, after a git clone:
python3 setup.py install
Use
Sequential mode
entropix sample \
--model /abs/path/to/dense/numpy/model.npy \
--vocab /abs/path/to/corresponding/model.vocab \
--dataset dataset_to_optimize_on \ # men, simlex or simverb
--shuffle \
--mode seq \
--kfold-size .2 \ # size of kfold, between 0 and .5
--metric pearson \ # spr(spearman), pearson, rmse or both (spr+rmse)
--num-threads 5
Limit mode
entropix sample \
--model /abs/path/to/dense/numpy/model.npy \
--vocab /abs/path/to/corresponding/model.vocab \
--dataset dataset_to_optimize_on \ # men, simlex or simverb
--mode limit \
--metric pearson \
--limit 10 # number of dimensions to sample
Project details
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entropix-2.0.1.tar.gz
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