Explain Machine Learning Models: Partial Dependence

Explain Machine Learning Models: Partial Dependence

Discussing ways to make your machine learning models more explainable to the average person. We look at the use of partial dependency in order to see how certain features affect predictions.

With all the complexity that comes with developing machine learning models, it comes as no surprise that some of these just don’t translate very well when being explained in plain English. The model inputs go in, the answers come out and no one knows how exactly the model arrived at this conclusion. This can result in some sort of disconnect or lack of transparency between different members working on the same team. As the prevalence of machine learning has increased in recent years, this lack of explainability when using complex models has grown even more. In this article, I’ll discuss a few ways to make your models more explainable to the average person whether they be your non-technical manager or just a curious friend.

machine-learning big-data developer programming software-development

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