方法证据记录
Explainable Naive Bayes
Explainable Naive Bayes extends the classic probabilistic Naive Bayes classifier with transparent, human-readable explanations of its predictions. By surfacing class priors, per-feature likelihoods, and log-odds contributions, it offers the interpretability demanded in high-stakes domains such as medicine, law, and education without sacrificing the simplicity and speed that make Naive Bayes a reliable baseline.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Explainable Naive Bayes Classifier
分类方法记录 · ml-model / machine-learning
- Rish, I. (2001). An empirical study of the naive Bayes classifier. In IJCAI Workshop on Empirical Methods in AI (pp. 41–46). · URL
- Naive Bayes classifier. Wikipedia. · URL
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