  This short paper aims to discuss the effectiveness and performance of
classical machine learning approaches for Human Activity Recognition (HAR). It
proposes two important models - Extra Trees and Stacked Classifier with the
emphasize on the best practices, heuristics and measures that are required to
maximize the performance of those models.
