They note that this metric induces a kernel function whose parameters are set entirely from the data.
mLKR can learn a weight matrix W for a mahalanobis metric that optimizes the leave-one out mean squared error of kernel regression (mSE), defined as: whereŷ i is estimated usingŷ j for all i = j, as in Eq.