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Bootstrap Confidence Intervals of Classification Error Rate for a Block of Missing Observations
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 Title & Authors
Bootstrap Confidence Intervals of Classification Error Rate for a Block of Missing Observations
Chung, Hie-Choon;
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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.
 Keywords
Bootstrap Confidence interval;error rate;block of missing observations;linear combination classification statistic;Jackknife method;Monte Carlo study;
 Language
English
 Cited by
 References
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