Universal consistency of the <i>k</i>-NN rule in metric spaces and Nagata dimension
Universal consistency of the <i>k</i>-NN rule in metric spaces and Nagata dimension
The k nearest neighbour learning rule (under the uniform distance tie breaking) is universally consistent in every metric space X that is sigma-finite dimensional in the sense of Nagata. This was pointed out by Cérou and Guyader (2006) as a consequence of the main result by those authors, combined with …