The ‘explainable’ bit means it is not a black box. With many kinds of machine learning, you don’t know the precise details of how the input data are transformed into the outputs. I used naive Bayes, which is basically maths. So you can trace the output back through the calculations to the inputs. This means the results can be explained and fully understand in terms of the input data. For my research it means I can understand why a particular object was classed as a young star, or as some other kind of object.
Thanks,
Andy