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GitHub / EpistasisLab / tpot

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EpistasisLab%2Ftpot

Stars: 9,519
Forks: 1,546
Open Issues: 290

License: lgpl-3.0
Language: Python
Repo Size: 76.1 MB
Dependencies: 29

Created: over 8 years ago
Updated: about 14 hours ago
Last pushed: 2 days ago
Last synced: about 10 hours ago

Commit Stats

Commits: 1876
Authors: 120
Mean commits per author: 15.63
Development Distribution Score: 0.771
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/EpistasisLab/tpot

Topics: adsp, ag066833, aiml, alzheimer, alzheimers, automated-machine-learning, automation, automl, data-science, feature-engineering, gradient-boosting, hyperparameter-optimization, machine-learning, model-selection, nia, parameter-tuning, python, random-forest, scikit-learn, u01ag066833

Files

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Readme

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Dependencies

.github/workflows/build-docs.yml actions

actions/checkout v2 composite
actions/setup-python v2 composite

.github/workflows/python-publish.yml actions

actions/checkout v2 composite
actions/setup-python v2 composite

optional-requirements.txt pypi

scikit-mdr ==0.4.4
skrebate ==0.3.4
torch ==1.3.1

requirements.txt pypi

deap >=1.2
imbalanced-learn >=0.7.0
joblib >=0.13.2
nose ==1.3.7
numpy >=1.16.3
pandas >=0.24.2
scikit-learn >=0.22.0
scipy >=1.3.1
stopit >=1.1.2
tqdm >=4.36.1
update-checker >=0.16
xgboost >=1.1.0

setup.py pypi

deap >=1.2
joblib >=0.13.2
numpy >=1.16.3
pandas >=0.24.2
scikit-learn >=0.22.0
scipy >=1.3.1
stopit >=1.1.1
tqdm >=4.36.1
update_checker >=0.16
xgboost >=1.1.0