The k-NN Identity Theorem Local Coherence and Classification Accuracy

We present the k-NN Identity Theorem: for k = 1, the semantic tolerance τ∗ equals the leave-one-out accuracy of 1-NN exactly. For k > 1, we derive concentration bounds under diagonal dominance conditions. We validate empirically on 6,743 datasets.