具有二元特征的朴素贝叶斯分类器的错误依赖关系。
Error-dependency relationships for the naïve Bayes classifier with binary features.
作者信息
Kuncheva Ludmila I, Hoare Zoë S J
机构信息
School of Computer Science, Bangor University, Sean Street, Bangor, Gwynedd, UK.
出版信息
IEEE Trans Pattern Anal Mach Intell. 2008 Apr;30(4):735-40. doi: 10.1109/TPAMI.2007.70845.
PMID:18276977
Abstract
We derive a tight dependency-related bound on the difference between the Naïve Bayes (NB) error and Bayes error for two binary features and two equiprobable classes. A measure of discrepancy of feature dependencies is proposed for multiple features. Its correlation with NB is shown using 23 real data sets.
摘要
我们推导了朴素贝叶斯（NB）误差与贝叶斯误差之间差异的紧密依赖关系边界，适用于两个二元特征和两个等概率类别。针对多个特征，提出了一种特征依赖差异的度量方法。使用23个真实数据集展示了它与朴素贝叶斯的相关性。
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