实验持续时间和超时空分析对脑电图分类方法的影响。

Simone Palazzo, Concetto Spampinato, Isaak Kavasidis, Daniela Giordano, Joseph Schmidt, Mubarak Shah
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引用次数: 0

摘要

Bharadwaj 等人[1]发表了一篇评论文章,利用随机类样本的平均脑电图数据评估了几种最先进方法的分类准确性。结果显示,其中一些方法达到了高于概率的准确度,而他们分析的目标--[2] 中提出的方法却没有达到。在这篇反驳文章中,我们将针对这些说法,解释为什么它们在认知神经科学文献中没有依据,以及为什么评估程序是无效和不公平的。
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The effects of experiment duration and supertrial analysis on EEG classification methods.

Bharadwaj et al. [1] present a comments paper evaluating the classification accuracy of several state-of-the-art methods using EEG data averaged over random class samples. According to the results, some of the methods achieve above-chance accuracy, while the method proposed in [2], that is the target of their analysis, does not. In this rebuttal, we address these claims and explain why they are not grounded in the cognitive neuroscience literature, and why the evaluation procedure is ineffective and unfair.

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