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Optimal Bayesian Classification When the Training Observations are Serially Dependent

机译:训练观测值与序列有关时的最佳贝叶斯分类

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摘要

In this study, we construct the optimal Bayesian classifier (OBC) when the training observations are serially dependent. To model the effect of dependency, we assume the training observations are generated from VAR(p), which is a multi-dimensional vector autoregressive process of order p.
机译:在这项研究中,当训练观察串行依赖时,我们构建最佳贝叶斯分类器(OBC)。为了模拟依赖性的效果,我们假设从VAR(P)产生训练观察,这是订单P的多维向量自回归过程。

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