<Dd> p (weight ∣ female) = 1.6789 ⋅ 10 − 2 (\ displaystyle p ((\ text (weight)) \ mid (\ text (female))) = 1.6789 \ cdot 10 ^ (- 2)) </Dd> <Dd> p (foot size ∣ female) = 2.8669 ⋅ 10 − 1 (\ displaystyle p ((\ text (foot size)) \ mid (\ text (female))) = 2.8669 \ cdot 10 ^ (- 1)) </Dd> <Dd> posterior numerator (female) = their product = 5.3778 ⋅ 10 − 4 (\ displaystyle (\ text (posterior numerator (female))) = (\ text (their product)) = 5.3778 \ cdot 10 ^ (- 4)) </Dd> <P> Since posterior numerator is greater in the female case, we predict the sample is female . </P>

Naïve bayesian classifier can be used only with categorical variables