AI Verify Fairness Metrics Toolbox (FMT) for Regression contains a list of fairness metrics used to measure how resources (e.g. opportunities, food, loan, medical help) are allocated among the demographic groups (e.g. married male, married female) given a set of sensitive feature(s) (e.g. gender, marital status). This plugin is developed for regression models.
Project description
Algorithm - Fairness Metrics Toolbox for Regression
Description
- The Fairness Metrics Toolbox (FMT) for Regression contains a list of fairness metrics used to measure how resources (e.g. opportunities, food, loan, medical help) are allocated among the demographic groups (e.g. married male, married female) given a set of sensitive feature(s) (e.g. gender, marital status). This plugin is developed for regression models.
License
- Licensed under Apache Software License 2.0
Developers:
- AI Verify
Installation
Each test algorithm can now be installed via pip and run individually.
pip install aiverify-fairness-metrics-toolbox-for-regression==2.0.0a1
Example Usage:
Run the following bash script to execute the plugin
#!/bin/bash
root_path="<PATH_TO_FOLDER>/aiverify/stock-plugins/user_defined_files"
python -m aiverify_fairness_metrics_toolbox_for_regression \
--data_path $root_path/data/sample_reg_pipeline_data.sav \
--model_path $root_path/pipeline/regression_tabular_donation \
--ground_truth_path $root_path/data/sample_reg_pipeline_ytest_data.sav \
--ground_truth donation \
--model_type REGRESSION \
--run_pipeline \
--sensitive_features_list gender
If the algorithm runs successfully, the results of the test will be saved in an output
folder.
Develop plugin locally
Execute the bash script below in the project root
#!/bin/bash
# setup virtual environment
python3 -m venv .venv
source .venv/bin/activate
# execute plugin
cd aiverify/stock-plugins/aiverify.stock.fairness-metrics-toolbox-for-regression/algorithms/fairness_metrics_toolbox_for_regression/
# install aiverify-test-engine
pip install -e .'[dev]'
python -m aiverify_fairness_metrics_toolbox_for_regression --data_path <data_path> --model_path <model_path> --ground_truth_path <ground_truth_path> --ground_truth <str> --model_type REGRESSION --run_pipeline --sensitive_features_list <list[str]>
Build Plugin
cd aiverify/stock-plugins/aiverify.stock.fairness-metrics-toolbox-for-regression/algorithms/fairness_metrics_toolbox_for_regression/
hatch build
Tests
Pytest is used as the testing framework.
Run the following steps to execute the unit and integration tests inside the tests/
folder
cd aiverify/stock-plugins/aiverify.stock.fairness-metrics-toolbox-for-regression/algorithms/fairness_metrics_toolbox_for_regression/
pytest .
Run using Docker
In the aiverify root directory, run the below command to build the docker image
docker build -t aiverify-fairness-metrics-toolbox-for-regression:v2.0.0a1 -f stock-plugins/aiverify.stock.fairness-metrics-toolbox-for-regression/algorithms/fairness_metrics_toolbox_for_regression/Dockerfile .
Run the below bash script to run the algorithm
#!/bin/bash
docker run \
-v $(pwd)/stock-plugins/user_defined_files:/input \
-v $(pwd)/output:/app/aiverify/output \
aiverify-fairness-metrics-toolbox-for-regression:v2.0.0a1 \
--data_path /input/data/sample_reg_pipeline_data.sav \
--model_path /input/pipeline/regression_tabular_donation \
--ground_truth_path /input/data/sample_reg_pipeline_ytest_data.sav \
--ground_truth donation \
--model_type REGRESSION \
--run_pipeline \
--sensitive_features_list gender
If the algorithm runs successfully, the results of the test will be saved in an output
folder in the working directory.
Tests
Pytest is used as the testing framework.
Run the following steps to execute the unit and integration tests inside the tests/
folder
docker run --entrypoint python3 aiverify-fairness-metrics-toolbox-for-regression:v2.0.0a1 -m pytest .
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