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GitHub / Kaleidophon / deep-significance

Enabling easy statistical significance testing for deep neural networks.

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Kaleidophon%2Fdeep-significance

Stars: 315
Forks: 20
Open Issues: 0

License: gpl-3.0
Language: Python
Repo Size: 5.54 MB
Dependencies: 39

Created: about 3 years ago
Updated: about 1 month ago
Last pushed: 7 months ago
Last synced: 6 days ago

Commit Stats

Commits: 187
Authors: 3
Mean commits per author: 62.33
Development Distribution Score: 0.032
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/Kaleidophon/deep-significance

Topics: compare-scores, deep-learning, deep-neural-networks, deeplearning, dl, hypothesis-testing, hypothesis-tests, machine-learning, machinelearning, ml, significance-testing, statistical-significance, statistical-significance-test

Files

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Readme

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Dependencies

docs/requirements-doc.txt pypi

dill >=0.3.4
joblib >=1.0.1
m2r >=0.2.1
mistune ==0.8.4
numpy >=1.19.5
numpydoc >=1.1.0
pandas >=1.3.3
psutil >=5.9.0
readme2tex >=0.0.1b2
recommonmark >=0.7.1
scipy >=1.6.0
sphinxbootstrap4theme >=0.6.0
sphinxemoji >=0.1.8
tqdm >=4.59.0

paper/paper_requirements.txt pypi

gym >=0.22.0
matplotlib >=3.4.3
notebook >=6.4.5
numpy >=1.19.5
pygame >=2.1.2
torch >=1.8.0

requirements-dev.txt pypi

coverage >=5.5
coveralls >=3.0.1
dill >=0.3.4
jax >=0.2.9
joblib >=1.0.1
numpy >=1.19.5
pandas >=1.3.3
psutil >=5.9.0
scipy >=1.6.0
tensorflow >=2.4.1
torch >=1.8.0
tqdm >=4.59.0

requirements.txt pypi

dill >=0.3.4
joblib >=1.0.1
numpy >=1.19.5
pandas >=1.3.3
psutil >=5.9.0
scipy >=1.6.0
tqdm >=4.59.0