Tutorial
Jun 26, 20269 min read
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Bayes Theorem
Most classifiers learn a direct mapping from features to class labels. Naive Bayes takes a different route: it models how each class generates features, then us…
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Naive Bayes
Tutorial
Jun 26, 202611 min read
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Variants of Naive Bayes
Bayes theorem gives the posterior $P(y \mid x) \propto P(y) \times P(x \mid y)$. To make this computable, you need a model for the likelihood $P(x \mid y)$ — ho…
Tutorial
Jun 26, 20266 min read
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Naive Bayes: Practical Implementation
Three variants, three datasets. This post runs each Naive Bayes classifier on the data it's designed for, inspects what the model learned, and shows exactly whe…