There are two key elements that make a model white-box: features have to be understandable, and the ML process has to be transparent. These models include linear and decision/regression tree models.

The opposite of a black box is a white box. Its results are transparent and can be analyzed by the user. The term black box model can be easily misused and may merely reflect a need to protect ...