# Naive Bayes for two continuous features

I have two features which are both continuous. How to perform a classification task based on them? I've read the Wikipedia entry on Naive Bayes, but this is only for discrete outcome and one feature.

• What is the outcome you want to classify?
– chl
Mar 24, 2012 at 9:36
• The outcome is discrete class (nominal). Mar 24, 2012 at 13:33
• Err, actually, not. The wikipedia page labels the features $F_1\ldots F_n$. Mar 24, 2012 at 13:48
• @fkr Does this question/answer help ?: stats.stackexchange.com/questions/4298/… Mar 24, 2012 at 19:58
• @ConjugatePrior Does it mean P(C).P(F1|C).P(F2|C) rather than P(C).P(F|C)? Mar 25, 2012 at 2:36

$$\text{posterior}(\text{male})=\frac{P(\text{male})P(\text{height}\mid\text{male})P(\text{weight}\mid\text{male})P(\text{footsize}\mid\text{male})}{\text{evidence}}$$
• Glad to hear it now makes sense. btw you don't have to post the image - you can write it in latex math notation, e.g. Bayes theorem is written p(C|F) = \frac{p(F|C) p(C)}{p(F)} which when you surround it with $ signs renders automatically as$p(C|F) = \frac{p(F|C) p(C)}{p(F)}\$. Mar 25, 2012 at 8:04