Explainable Decision Forest
From ISLAB/CAISR
| Title | Explainable Decision Forest |
|---|---|
| Summary | Designing an explainable decision forest classifier for fault detection |
| Keywords | decision forest, explainable AI, fault detection |
| TimeFrame | Autumn 2023 |
| References | |
| Prerequisites | |
| Author | |
| Supervisor | Hamid Sarmadi, Sepideh Pashami, Sławomir Nowaczyk |
| Level | |
| Status | Open |
An algorithm to train separate "explainable" decision trees for detecting different types of fault has been developed. We would like to extend the algorithm to an ensemble (Decision Forest) method when decision trees are aware of each other.
You can read more about the original algorithm in the following link: https://hhse-my.sharepoint.com/:b:/g/personal/hamid_sarmadi_hh_se/EWlwNDHNrnNMqBQ93dNdu9kBS61tWwF56a-rI7A-kPEpRA?e=EpEFQn
