Feature selection of non-intrusive load monitoring system using RFE and RF

Abstract

Feature selection is a process of selecting relevant features and removing the irrelevant and redundant ones based on certain specific criteria in the original date set. This paper proposes the random forest algorithm (RF) based on recursive feature elimination (RFE) to select features in non-intrusive load monitoring system. Adopting the random forest algorithm as the basic approach, we repeatedly build models and filter features to identify the best subset of features. Last, the results of experiments using public data sets verify the effectiveness of the proposed algorithm.