MIXTURE OR LOGISTIC-REGRESSION ESTIMATION FOR DISCRIMINATION

被引：0
|
作者：
ONEILL, TJ
机构：
[1] Department of Statistics, Faculty of Economics and Commerce, Australian National University, Canberra
来源：
STATISTICS & PROBABILITY LETTERS | 1994年 / 20卷 / 02期
关键词：
LOGISTIC REGRESSION; MIXTURES; UNCLASSIFIED OBSERVATIONS;
D O I：
10.1016/0167-7152(94)90029-9
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
When a training sample for a classification rule includes unclassified observations, the estimation can be done by maximum likelihood using both the classified and unclassified data (GM) or (assuming an exponential family) by logistic regression (L) on the classified data only. This paper shows that the choice depends on the separation and shape of the family.
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页码：139 / 142
页数：4
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