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Body surface potential map classifications: trade-off in group representations

机译:身体表面潜在地图分类:集体表现中的权衡

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For the overall quality, Q, of statistical body surface potential map (BSPM) characterisation the product of the Karhunen-Loeve (K-L) domain representation accuracy, A, and the reliability of the group conditional probability function representation R, were introduced. Reliability R, was computed according to the Kolmogorov-Smirnov distance definition taken for the optimal projections in the sense of the Sebestyen transformation and for the projection providing optimal separation of two sample sets taken from the same continuous probability distributions. Results show that at a finite set of the learning samples, Q has a peaking character for both R definitions, i.e. above and below of the optimal K-L domain dimensionality, M, the overall quality of statistical group representation deteriorates. According to the criteria formulated, current BSPM databases are small for estimating the clinical utility of maps.
机译:对于整体质量,Q,统计体表潜在地图(BSPM)表征Karhunen-Loeve(K-L)域表示精度,A和组条件概率函数表示R的可靠性。根据Kolmogorov-Smirnov距离定义计算可靠性R,用于在Sebestyen转换的意义上进行最佳突起以及从相同的连续概率分布所采取的两个样品集的最佳分离。结果表明,在有限的学习样本中,Q具有峰值的峰值特性,即R定义,即最佳K-L结构域维度,M,统计组表示的整体质量恶化。根据配方标准,当前BSPM数据库很小,用于估计地图的临床效用。

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