AI Verify implementation of Partial Dependence Plot (PDP) that explains how each feature and its feature value contribute to the predictions.
Project description
Algorithm - Partial Dependence Plot
Description
- A Partial Dependence Plot (PDP) explains how each feature and its feature value contribute to the predictions.
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-partial-dependence-plot
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_partial_dependence_plot \
--data_path $root_path/data/sample_bc_credit_data.sav \
--model_path $root_path/model/sample_bc_credit_sklearn_linear.LogisticRegression.sav \
--ground_truth_path $root_path/data/sample_bc_credit_data.sav \
--ground_truth default \
--model_type REGRESSION \
--no-run_pipeline
If the algorithm runs successfully, the results of the test will be saved in an output folder.
Develop plugin locally
Assuming aiverify-test-engine has already been installed in the virtual environment, run the following bash script to install the plugin and execute a test:
#!/bin/bash
# setup virtual environment
python3 -m venv .venv
source .venv/bin/activate
# install plugin
cd aiverify/stock-plugins/aiverify.stock.partial-dependence-plot/algorithms/partial_dependence_plot/
pip install .
python -m aiverify_partial_dependence_plot --data_path <data_path> --model_path <model_path> --ground_truth_path <ground_truth_path> --ground_truth <str> --model_type CLASSIFICATION --run_pipeline
Build Plugin
cd aiverify/stock-plugins/aiverify.stock.partial-dependence-plot/algorithms/partial_dependence_plot/
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.partial-dependence-plot/algorithms/partial_dependence_plot/
pytest .
Run using Docker
In the aiverify root directory, run the below command to build the docker image
docker build -t aiverify-partial-dependence-plot -f stock-plugins/aiverify.stock.partial-dependence-plot/algorithms/partial_dependence_plot/Dockerfile .
Run the below bash script to run the algorithm
#!/bin/bash
docker run \
-v $(pwd)/stock-plugins/user_defined_files:/input \
-v $(pwd)/stock-plugins/aiverify.stock.partial-dependence-plot/algorithms/partial_dependence_plot/output:/app/aiverify/output \
aiverify-partial-dependence-plot \
--data_path /input/data/sample_bc_credit_data.sav \
--model_path /input/model/sample_bc_credit_sklearn_linear.LogisticRegression.sav \
--ground_truth_path /input/data/sample_bc_credit_data.sav \
--ground_truth default \
--model_type REGRESSION \
--no-run_pipeline
If the algorithm runs successfully, the results of the test will be saved in an output folder in the algorithm 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 \
-w /app/aiverify/stock-plugins/aiverify.stock.partial-dependence-plot/algorithms/partial_dependence_plot \
aiverify-partial-dependence-plot \
-m pytest .
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