https://github.com/dataiku/dss-plugin-model-data-compliance

Automatically check if new incoming data conforms the original training data
https://github.com/dataiku/dss-plugin-model-data-compliance

Last synced: 6 days ago
JSON representation

Automatically check if new incoming data conforms the original training data

• Host: GitHub
• URL: https://github.com/dataiku/dss-plugin-model-data-compliance
• Owner: dataiku
• License: mit
• Created: 2020-07-07T15:21:53.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2025-05-07T16:15:14.000Z (11 months ago)
• Last Synced: 2025-05-07T17:26:18.834Z (11 months ago)
• Language: Python
• Size: 73.2 KB
• Stars: 1
• Watchers: 22
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# Model Data Compliance

⚠️ Starting with DSS version 14 this plugin is considered "deprecated".

For proper monitoring of deployed ML models, a considerate data scientist/ML engineer want to check new data looks like training data.

## Scope of the plugin

This plugin offers a set of different DSS components to monitor input data:

* Custom metric: compute compliance metrics given a reference dataset or a saved model.

* Custom check: validate new data given a reference dataset or a saved model.

## Installation and requirements

Please see our [official plugin page](https://www.dataiku.com/product/plugins/model-data-compliance/) for installation.

## Changelog

**Version 1.0.0 (2020-08)**

* Initial release

* Custom metric to compute compliance metrics

* Custom check to validate new data based on compliance metrics

You can log feature requests or issues on our [dedicated Github repository](https://github.com/dataiku/dss-plugin-model-data-compliance/issues).

# License

The Model drift monitoring plugin is:

   Copyright (c) 2020 Dataiku SAS

   Licensed under the [MIT License](LICENSE.md).