Adapter [/əˈdaptə/] noun, a device for connecting pieces of equipment that cannot be connected directly.
This is a collection of tools that serve to make the Java implementation of the Anchors algorithm more easy to use. The algorithm (as introduced Marco Tulio Ribeiro, 2018) is model-agnostic, but the nature of the dataset needs to be considered.
This repository includes methodological aspects, i.e. default approaches on how to apply the algorithm to tabular data in typical use cases with tabular data (such as bpmn.ai), images or texts as well as technical aspects, such as running Anchors explanations on Apache Spark.
This project is to be considered research-in-progress.
For more information on Anchors and this implementation, see main repository.
Examples of using the Anchors implementation and its various adapters are provided within the XAI Examples repository. Please refer to this project for tutorials and easy-to-run applications.
The project is operated and further developed by the viadee Consulting AG in Münster, Westphalia. Results from theses at the WWU Münster and the FH Münster have been incorporated.
- Further theses are planned: Contact person is Dr. Frank Köhne from viadee. Community contributions to the project are welcome: Please open Github-Issues with suggestions (or PR), which we can then edit in the team. For general discussions please refer to the main repository.
- We are looking for further partners who have interesting process data to refine our tooling as well as partners that are simply interested in a discussion about AI in the context of business process automation and explainability.