I'm using scikit-learn in Python to develop a classification algorithm to predict gender of a certain customers. Amongst others I want to use the Naive Bayes classifier but my problem is that I have a mix of categorial data (ex: "Registered online", "Accepts email notifications" etc) and continuous data (ex: "Age", "Length of membership" etc). I haven't used scikit much before but I suppose that that Gaussian Naive Bayes is suitable for continuous data and that Bernouilli Naive Bayes can be used for categorial data. However, since I want to have both categorical and continuous data in my model, I don't really know how to handle this. Any ideas would be much appreciated!