Assessment of fisher and logistic linear and quadratic discrimination models
Assessment of fisher and logistic linear and quadratic discrimination models
复制标题
渔民和逻辑线性和二次判别模型的评估
DOI：
10.1016/0167-9473(83)90099-3
复制
发表时间：
1983
影响因子：
1.8
通讯作者：
G. McCabe
中科院分区：
文献类型：
--
作者：
C. Bayne;J. Beauchamp;V. E. Kane;G. McCabe
本文总结了Fisher和logistic线性和二次判别函数性能比较研究的结果。研究了三种类型的二元分布。将每个分类规则与不同数据类型的最优最大似然过程进行比较。直接计算了样本判别函数的理论误分类概率，并用于比较不同程序在偏差和变异方面的差异。总结和建议，以协助应用统计学家作出正确选择的歧视程序和本研究的结果与早期的调查进行比较。本研究表明，判别函数形式的说明可能是判别分析中最重要的部分之一。
This paper summarizes the results from a study comparing the performance of the Fisher and logistic linear and quadratic discriminant functions. Three types of bivariate distributions are studied. Each classification rule is compared to the optimal maximum likelihood procedure for the different data types. The theoretical misclassification probabilities of the sample discriminant functions are calculated directly and used for the comparison of the different procedures both in terms of bias and variation. Generalizations and recommendations are made to assist the applied statistician in making the correct choice of a discrimination procedure and the results of this study are compared with earlier investigations. This study shows that specification of the form of the discriminant function may be one of the most important parts of a discriminant analysis.