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What is Bayes Optimal Classifier Explained about?
The document covers Bayesian Learning, focusing on Bayes theorem and its components, including conditional, prior, and posterior probabilities, as well as likelihood and marginal probabilities. It also discusses the Bayes Optimal Classifier and Naïve Bayes classifier, along with examples illustrating their applications in probability calculations. Additionally, the document introduces Bayesian belief networks and the Expectation-Maximization algorithm.
- Author
- Deepanshu Tyagi
- Language
- EN