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A comparison of performance metrics for event classification in Non-Intrusive Load Monitoring

机译:非侵入式负载监控中事件分类的性能指标比较

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In this work, we analyse experimentally the behaviour of 18 different performance metrics when applied to classification algorithms in event-based Non-Intrusive Load Monitoring, identifying relationships and clusters between the measures. Our results indicate that performance metrics have more in common than what was initially expected. Our results also suggest that in this multi-class classification problem, researchers should avoid micro-average and unweighted macro-average metrics in favor of their weighted macro-average counterparts. Finally, the results also suggest that probabilistic measures can provide important information that is not available when using more traditional performance metrics.
机译:在这项工作中,我们将实验性地分析18种不同性能指标的行为,将其应用于基于事件的非侵入式负载监控中的分类算法,确定度量之间的关系和集群。我们的结果表明,性能指标比最初预期的要多。我们的结果还表明,在这个多类别分类问题中,研究人员应避免使用微观平均和未加权的宏观平均指标,而应使用加权的宏观平均指标。最后,结果还表明,概率度量可以提供使用传统绩效指标时无法获得的重要信息。

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