Estimation of the conditional risk in classification: The swapping method

摘要: The bias of the empirical error rate in supervised classification is studied. It shown that this can be understood as a covariance between rule and labeling training data. From result, new penalized criterion proposed to perform model selection classification. Applications resulting algorithm simulated real data are presented.