smclarify 0.1

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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.