In machine learning, there are currently debates about what an explanation or explainable model is and what is necessary for a given purpose. This post details the concepts of explanation and interpretation to help clarify the difference between the two; discusses how, although interpretation is preferable, explanation is the only option for many machine learning techniques; and then details a clustering technique that aids explanation for unsupervised machine learning.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.