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What is Understanding Bayesian Learning and Naïve Bayes about?
Bayesian Learning involves using Bayes Theorem to determine the most probable hypothesis based on observed training data and prior probabilities. The Naïve Bayes Classifier is a classification technique that assumes all predictors are independent, allowing for efficient predictions based on maximum a posteriori estimates. While it is easy to implement and performs well with categorical data, it has limitations such as zero probability issues with unseen categories and the unrealistic assumption of independe
- Author
- nahimalumja
- Language
- EN