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Lecture
Naive Bayes: Gaussian Discriminant Analysis
Description
This lecture covers the Naive Bayes assumption for modeling a system with 50,000 possible outcomes, extending it to non-binary features. It discusses Gaussian Discriminant Analysis, ML estimates with Laplace smoothing, and the Kernel trick to reduce computational complexity.
Official source
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