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Parameter estimation of linear function using VUS and HUM maximization
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 Title & Authors
Parameter estimation of linear function using VUS and HUM maximization
Hong, Chong Sun; Won, Chi Hwan; Jeong, Dong Gil;
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Consider the risk score which is a function of a linear score for the classification models. The AUC optimization method can be applied to estimate the coefficients of linear score. These estimates obtained by this AUC approach method are shown to be better than the maximum likelihood estimators using logistic models under the general situation which does not fit the logistic assumptions. In this work, the VUS and HUM approach methods are suggested by extending AUC approach method for more realistic discrimination and prediction worlds. Some simulation results are obtained with both various distributions of thresholds and three kinds of link functions such as logit, complementary log-log and modified logit functions. It is found that coefficient prediction results by using the VUS and HUM approach methods for multiple categorical classification are equivalent to or better than those by using logistic models with some link functions.
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AUC 최적화를 이용한 낮은 부도율 자료의 모수추정,홍종선;원치환;

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