Advanced Machine Learning with R

Model interpretability

Often, in a business environment when ML models are built, just reporting the performance measurements obtained to confirm the goodness of the model may not be enough. The stakeholders generally are inquisitive to understand the whys of the model, that is, what are the factors contributing to the model's performance? In other words, the stakeholders want to understand the causes of the effects. Essentially, the expectation from the stakeholders is to understand the importance of various features in the model and the direction in which each of the variables impacts the model.

For example, does a feature of time spent on exercising every day in the dataset for a cancer prediction model have any impact on the model predictions ...