An empirical measure that results from the nearest neighbors to a given point - the nearest neighbor measure - is introduced and studied as a central statistical quantity. First, the resulting empirical process is shown to satisfy a uniform central limit theorem under a (local) bracketing entropy condition on the underlying class of functions (reflecting the localizing nature of nearest neighbor algorithm). Second a uniform non-asymptotic bound is established under a well-known condition, often refereed to as Vapnik-Chervonenkis, on the uniform entropy numbers.

翻译：从最近的邻居到某一点得出的一项经验性衡量标准,即最近的邻居测量标准,作为中央统计数量加以介绍和研究。首先,由此得出的经验性程序显示,在(当地)分类的参数范围内,符合一个统一的中央理论限制,取决于基本功能类别(反映最近的邻居算法的本地化性质),第二,在众所周知的条件下建立了统一的非无药性约束,通常称为Vapnik-Chervonenkis, 指统一的信箱编号。