A strategy for computing the parameters of k-NN

Abstract

This paper presents some details about a strategy used to compute the two important parameters needed for time series prediction using k-Nearest Neighbor: the number of neighbors considered and the length of the suffix taken into account. The given method can be used for univariate time series prediction and is inspired by machine learning techniques.