Explanation in Machine Learning

Abstract

The innovations of highly accurate machine learning models (such as deep neural networks) boosted their use in society. However, the structures of such high-end models are highly complex and it is difficult to understand their inference processes nor decision criteria. In this paper, I introduce some popular approaches for explaining the decisions of complex machine learning models.