Machine learningMachine learning

正则化朴素贝叶斯

正则化朴素贝叶斯通过显式的平滑或收缩（最常见的是拉普拉斯（加性）平滑）来增强经典的朴素贝叶斯概率分类器，以防止对未见特征值产生零概率估计并减少过拟合。其结果是一个快速、鲁棒的分类器，与未平滑的朴素贝叶斯相比，泛化能力更好，尤其是在文本等稀疏或高维数据上。

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正则化朴素贝叶斯

Rennie, J. D. M., Shih, L., Teevan, J., & Karger, D. R. (2003). Tackling the poor assumptions of Naive Bayes text classifiers. In Proceedings of the 20th International Conference on Machine Learning (ICML-2003), pp. 616–623. link ↗
Naive Bayes classifier. Wikipedia. link ↗

ScholarGate. (2026, June 3). Regularized Naive Bayes Classifier. ScholarGate. https://scholargate.app/zh/machine-learning/regularized-naive-bayes

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.