Machine learningMachine learning
贝叶斯朴素贝叶斯 (Bayesian Naive Bayes)
贝叶斯朴素贝叶斯对经典朴素贝叶斯分类器参数进行了完全贝叶斯处理：它不对类别条件分布进行最大似然估计，而是对参数放置共轭先验（通常是分类数据的狄利克雷分布，连续数据的正态-伽马分布），然后将它们积分掉，从而产生自然量化不确定性并避免在小型数据集上过拟合的预测后验分布。
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来源
- Murphy, K. P. (2012). Machine Learning: A Probabilistic Perspective (Ch. 3, 4). MIT Press. ISBN: 978-0-262-01802-9
- Bishop, C. M. (2006). Pattern Recognition and Machine Learning (Ch. 8). Springer. ISBN: 978-0-387-31073-2
如何引用本页
ScholarGate. (2026, June 3). Fully Bayesian Naive Bayes Classifier. ScholarGate. https://scholargate.app/zh/machine-learning/bayesian-naive-bayes
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