APPLICATION OF BIAS TO DISCRIMINANT-ANALYSIS
APPLICATION OF BIAS TO DISCRIMINANT-ANALYSIS
复制标题
DOI：
10.1080/03610927608827401
复制
发表时间：
1976-01-01
期刊：
影响因子：
--
通讯作者：
DIPILLO, PJ
中科院分区：
文献类型：
--
作者：
DIPILLO, PJ
当使用样本估计构造分类规则时，误分类的概率并没有最小化。本文引入了一个有偏最小X2规则来对多元正态总体中的项目进行分类。利用方差减小的原理，降低了有偏过程中的误分类概率。在广泛的条件下的采样实验的结果，以证明这种改进。
When classification rules are constructed using sample estimatest it is known that the probability of misclassification is not minimized. This article introduces a biased minimum X2rule to classify items from a multivariate normal population. Using the principle of variance reduction, the probability of misclassification is reduced when the biased procedure is employed. Results of sampling experiments over a broad range of conditions are provided to demonstrate this improvement.