K-nearest neighbor algorithm for univariate time series prediction

Abstract

The paper contains a description of a k-nearest neighbor-based method used for the univariate time series prediction problem. The method presented is inspired by machine learning techniques used for classification, here extended to perform regression. Experimental results and comparisons with the predicted values obtained by ARIMA show a good behavior of this approach.