We consider multivariate regression smoothing through a conditional mean shift procedure. By computing local conditional means iteratively over a set or grid of target points, at each iteration a `net' is formed which gently drifts towards the data cloud, until it settles at the conditional modes of the response distribution.
The method is edge-preserving and allows for multi-valued response
