Does scikit learn include a Naive Bayes classifier with continuous inputs?

Question

Is there anything in scikit learn that can help me with the following?

I need a Bayesian network that is capable of taking continuous valued inputs and training against continuous valued targets. I then want to feed in new, previously unseen continuous inputs and receive estimates of the target values. Preferably with a way to measure confidence of the predictions. (PDFs perhaps?)

I am uncertain whether this would be considered a Naive Bayes Classifier or not.

I keep looking at GaussianNB but I just cannot see how it could be used in this way.

I'd like one that support "independence of irrelevant alternatives"

Any advice is greatly appreciated.

Answer 1

You are talking about regression, not classification. Naive Bayes Classifier is not a regression model. Check out numerous scikit-learn's regressors. IN particular, your could be interested in Bayesian Ridge Regression.