Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Bootstrap Confidence Intervals of Classification Error Rate for a Block of Missing Observations

  • Published : 2009.07.31
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Abstract

In this paper, it will be assumed that there are two distinct populations which are multivariate normal with equal covariance matrix. We also assume that the two populations are equally likely and the costs of misclassification are equal. The classification rule depends on the situation when the training samples include missing values or not. We consider the bootstrap confidence intervals for classification error rate when a block of observation is missing.

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References

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