方法证据记录
Robust Naive Bayes
Robust Naive Bayes extends the standard Naive Bayes classifier to handle uncertainty or noise in class-conditional probability estimates by replacing point probability estimates with intervals or sets of distributions. The canonical formulation — the Naive Credal Classifier proposed by Zaffalon (2002) — uses imprecise-probability sets so that predictions are made only when all distributions in the set agree, withholding a label when evidence is insufficient.
源记录
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Robust Naive Bayes Classifier
分类方法记录 · ml-model / machine-learning
- Zaffalon, M. (2002). The Naive Credal Classifier. Journal of Statistical Planning and Inference, 105(1), 5–21. · DOI 10.1016/S0378-3758(01)00201-4
- Naive Bayes classifier. Wikipedia. · URL
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