Introduction

In this episode, i speak with lucas mertino about his work on explainable camens. The result of solving a camens problem is a set of boundaries that define which cluster to associate any new data points with as they arrive. In higher dimensions than that, where your data has many more features, there is no guarantee the resulting classify ation will be intuitive or easy to explain in common parlance.