I was reading Freidman's book "The elements of statistical learning-2nd edition". Page 365, it talks about partial dependence plot. I don't quite understand how he actually calculates partial depence of f(X) on Xs. Say, I built a model on 4 predictors; I use the model itself as f(Xs,Xc). I want to know the partial dependence of my first predictor V1. If the data looks like :<p>
V1 V2 V3 V4 predicted_p <p>
1 1 0 1 0.2<p>
1 2 0 0 0.24<p>
2 1 1 1 0.6<p>
2 2 0 1 0.4<p>
Is the partial dependence for V1 has two values, one for V1=1, the other for V1=2?
For case V1=1, PD=(0.2+0.24)/2=0.22; for case V1=2, PD=(0.6+0.4)/2=0.5
<p>
Do I understand right? Thank you.

Besides, are the mean of partial dependence for each predictor equal?