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Machine Learning: The Engineering Approach
Module 11 of 13
11. Naive Bayes (Spam Filtering)
1. Bayes' Theorem
$$ P(A|B) = \frac{P(B|A)P(A)}{P(B)} $$ It calculates the probability of a label given the features.
2. Why "Naive"?
It assumes all features are independent. "Password" and "Reset" are treated as if they have nothing to do with each other. Despite this "naive" assumption, it is blazing fast and effective for text.