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Naïve Assumption In Machine Learning

This article describes the naïve assumption.

What Does Naïve Assumption State?

The model assumes that all features (variables) are independent of each other, given the class label.

Example

Let us say we are predicting whether an email is Spam or Not Spam.The features are: -

F1 = whether the email contains the word "discount".
F2 = whether the email contains the word "offer".

Now, in real life, F1 and F2 are correlated (emails with discount often have offer).

But Naïve Bayes, says that if we already know the class = Spam, then the probability of seeing discount is independent of the probability of seeing offer.

Posted By -	Karan Gupta

Posted On -	Monday, September 29, 2025

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