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Project description
smclarify
Amazon Sagemaker Clarify
Bias detection and mitigation for datasets and models.
Terminology
Facet
A facet is column or feature that will be used to measure bias against. A facet can have value(s) that designates that sample as "sensitive".
Label
The label is a column or feature which is the target for training a machine learning model. The label can have value(s) that designates that sample as having a "positive" outcome.
Bias measure
A bias measure is a function that returns a bias metric.
Bias metric
A bias metric is a numerical value indicating the level of bias detected as determined by a particular bias measure.
Bias report
A collection of bias metrics for a given dataset or a combination of a dataset and model.
Development
virtualenv -p(which python3) venv
source venv/bin/activate.fish
pip install -e .[test]
pytest --pspec
pre-commit install && pre-commit run --all-files
Always run pre-commit run --all-files
before commit.
For running unit tests, do ./test.sh
or pytest --pspec
. If you are using PyCharm, and cannot see the green run button next to the tests, open Preferences
-> Tools
-> Python Integrated tools
, and set default test runner to pytest
.
Project details
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