论文标题
人类活动识别的累积概括
Stacked Generalization for Human Activity Recognition
论文作者
论文摘要
这篇简短的论文旨在讨论人类活动识别的经典机器学习方法的有效性和性能（HAR）。它提出了两个重要的模型 - 额外的树木和堆叠的分类器，强调最佳实践，启发式方法和措施，这些实践，措施和措施最大化这些模型的性能。
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.
