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AI Verify implementation of the Accumulated Local Effect algorithm. The algorithm provides black box explainations of how features and their corresponding values influence the prediction of a model.

Project description

Algorithm - Accumulated Local Effect

Description

  • Performs ALE Discrete and ALE Continuous computation

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-accumulated-local-effect

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_accumulated_local_effect \
    --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 CLASSIFICATION

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
python -m venv .venv
source .venv/bin/activate

# install plugin
cd aiverify/stock-plugins/aiverify.stock.accumulated-local-effect/algorithms/accumulated_local_effect/
pip install .

python -m aiverify_accumulated_local_effect --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.accumulated-local-effect/algorithms/accumulated_local_effect/
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.accumulated-local-effect/algorithms/accumulated_local_effect/
pytest .

Run using Docker

In the aiverify root directory, run the below command to build the docker image

docker build -t aiverify-accumulated-local-effect -f stock-plugins/aiverify.stock.accumulated-local-effect/algorithms/accumulated_local_effect/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.accumulated-local-effect/algorithms/accumulated_local_effect/output:/app/aiverify/output \
    aiverify-accumulated-local-effect \
    --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 CLASSIFICATION

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 aiverify-accumulated-local-effect -m pytest .

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