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>Figure 1: Mean accuracy $ar {m chi} $ of the Bayesian classification approach (solid lines) and of the majority voting using the same sequence of volunteers (dotted lines) (A) and percentage of trials where the Bayesian approach outperforms majority voting (B) as a function of the mean average number of volunteers $ar {m u} $ used for classification.
【2h】
Figure 1: Mean accuracy $ar {m chi} $ of the Bayesian classification approach (solid lines) and of the majority voting using the same sequence of volunteers (dotted lines) (A) and percentage of trials where the Bayesian approach outperforms majority voting (B) as a function of the mean average number of volunteers $ar {m u} $ used for classification.
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机译：图1：平均准确性$ bar { rm chi} $的贝叶斯分类方法（实线）和使用相同的志愿者（虚线）（a）和贝叶斯方法的试验百分比的大多数投票优于大多数投票（b）作为用于分类的平均平均志愿者的平均平均数量的函数。
