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GitHub / Trusted-AI / AIF360
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Trusted-AI%2FAIF360
Stars: 2,314
Forks: 815
Open Issues: 192
License: apache-2.0
Language: Python
Repo Size: 6.51 MB
Dependencies:
46
Created: almost 6 years ago
Updated: about 1 month ago
Last pushed: about 1 month ago
Last synced: 29 days ago
Commit Stats
Commits: 339
Authors: 71
Mean commits per author: 4.77
Development Distribution Score: 0.628
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/Trusted-AI/AIF360
Topics: ai, artificial-intelligence, bias, bias-correction, bias-detection, bias-finder, bias-reduction, codait, deep-learning, discrimination, fairness, fairness-ai, fairness-awareness-model, fairness-testing, ibm-research, ibm-research-ai, machine-learning, python, r, trusted-ai
Files
Dependencies
- actions/checkout v3 composite
- actions/setup-python v3 composite
- r-lib/actions/setup-r v2 composite
- reticulate * imports
- rstudioapi * imports
- testthat * suggests
- pytorch/pytorch latest build
- com.ibm.aif360:nifi-aif360-processors 1.0-SNAPSHOT
- commons-io:commons-io 2.7
- org.apache.nifi:nifi-api
- org.apache.nifi:nifi-utils 1.11.0
- junit:junit test
- org.apache.nifi:nifi-mock 1.11.0 test
- org.slf4j:slf4j-simple test
- fairlearn >=0.7.0
- jinja2 ==3.0.3
- pytest >=3.5.0
- sphinx ==1.8.6
- sphinx_rtd_theme ==0.4.3
- BlackBoxAuditing *
- adversarial-robustness-toolbox >=1.0.0
- cvxpy >=1.0
- fairlearn >=0.7.0
- igraph ==0.9.8
- inFairness >=0.2.2
- ipympl *
- jinja2 ==3.0.3
- jupyter *
- lightgbm ==3.1.1
- lime *
- pytest >=3.5.0
- pytest-cov >=2.8.1
- rpy2 ==3.4.5
- seaborn *
- skorch ==0.11.0
- sphinx ==1.8.6
- sphinx_rtd_theme ==0.4.3
- tempeh *
- tensorflow >=1.13.1
- torch *
- tqdm *
- matplotlib *
- numpy >=1.16
- pandas >=0.24.0
- scikit-learn >=1.0
- scipy >=1.2.0