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for some constants <math> B_1 </math> and <math> B_2 </math>.
The choice <math>k^* = \left\lfloor B n^{\frac 4 {d+4}} \right\rfloor</math> offers a trade off between the two terms in the above display, for which the <math>k^*</math>-nearest neighbour error converges to the Bayes error at the optimal ([[minimax]]) rate <math>\mathcal{O}\left(n^{-\frac 4 {d+4}}\right)</math>.
==Metric learning==
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