Explainability Tests

Partial Dependence Plot is a type of Explainability test. To execute this test against your model, you will need to upload data and upload model onto the portal.

Run using portal

Click on HomePage > Manage > Test Results > "Run New Test"

Choose the following options:

• Algorithm: aiverify_partial_dependence_plot
• Model: sample_bc_credit_sklearn_linear.LogisticRegression.sav
• Test Dataset: sample_bc_credit_data.sav
• Ground Truth Dataset: sample_bc_credit_data.sav
• Ground Truth Column: default

Click on "Run Test"

You can confirm the status of the test run on the portal.

Run using Command Line (CLI) interface

Install the test using pip:

pip install aiverify-partial-dependence-plot

Run the 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.LogisticRestression.sav \
  --ground_truth_path $root_path/data/sample_bc_credit_data.sav \
  --ground_truth default \
  --model_type REGRESSION \
  --no-run_pipeline

Refer to Python notebook that walks through the steps with sample data.

Once the algorithm runs successfully, the results will be saved in an output folder. Use the generated result to create a report.

Generate report

To generate report using the test results, select

HomePage > Create New Project > Create New Report Template.

Select "Partial Dependence Plot" on the left pane and pick the 3 widgets and load them onto the canvas and click "Next".

Choose the model and test results from previous run and click "Next".

Save the report or export as a PDF.

Info

Report generation is optimised for Chrome browser. Users are recommended to use Chrome browser for best experience compared to other browsers.