Stacked Generalization for Human Activity Recognition

Abstract

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.