Course Content

  • 4_6_Naive_Bayes_Classifier

Course Content

FAQs

The Naive Bayes Classifier is a basic and effective classification method that aids in the development of fast machine learning models capable of making quick predictions. It's a probabilistic classifier, which means it makes predictions based on an object's probability.

Although intractable, the conditional probability can be determined using the joint probability. The Bayes Theorem establishes a consistent method for estimating conditional probability. The computation for Bayes Theorem in its simplest version is as follows: P(A|B) = P(B|A) * P(A) / P(A) / P(A) / P(A) / P(A) / P(A) (B)

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