An affine invariant k-nearest neighbor regression estimate

We propose a new k-NN regression estimate based on a data-dependent metric in R^d which is used to define the k-nearest neighbors of a given point. The metric is invariant under all affine transformations. With this metric, the standard k-nearest neighbor regression estimate is asymptotically consistent under the usual conditions on k, and minimal requirements on the input data.