Partial dependence

Partial dependence is a measure of the average model prediction with respect to an input variable. Partial dependence plots display how machine-learned response functions change based on the values of an input variable of interest while taking nonlinearity into consideration and averaging out the effects of all other input variables. It shows whether the relationship between the target and a variable is linear, monotonic or more complex.