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The small-n-large-P situation has become common in genetics research, medical studies, risk management, and other fields. Feature selection is crucial in these studies yet poses a serious challenge. The traditional criteria such as AIC, BIC, and crossvalidation choose too many features. To overcome the difficulties caused by the small-n-large-P situation, Chen and Chen (2008) developed a family of extended Bayes information criteria (EBIC). Under normal linear models, EBIC is found to bedoi:10.5705/ss.2010.216 fatcat:lszurrcxdjgr5jheewgzsabbxi