The Optimality of Naive Bayes
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Summary
A sufficient condition for the optimality of naive Bayes is presented and proved, in which the dependence between attributes do exist, and evidence that dependence among attributes may cancel out each other is provided.
- Type
- article
- Published
- 2004-01-01
- Cited by
- 2,005
- References
- 18
- OpenAlex
- https://openalex.org/W349770100
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:8891634
Keywords
Naive Bayes classifier, Machine learning, Bayesian programming, Bayes error rate, Artificial intelligence
References
- Learnability of Augmented Naive Bayes in Nonimal Domains
- Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier
- Naive Bayes for regression
- Assessing the Calibration of Naive Bayes Posterior Estimates
- An Analysis of Bayesian Classifiers
- A Bayesian Network Classifier that Combines a Finite Mixture Model and a NaIve Bayes Model
- On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality
- Idiot's Bayes—Not So Stupid After All?
- C4.5: Programs for Machine Learning
- Searching for Dependencies in Bayesian Classifiers
- Towards a Better Understanding of Memory-based Reasoning Systems
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