I am looking for a classification algorithm that emits probabilities for each label and supports real-valued features.
1) From what I gather, logistic regression may output a variable in $(0, 1)$, however, it does not describe the true classification probability.
2) Naive Bayes supports probabilities, however, it uses discrete features.
I need this to compute expected utilities. There is no way to couple utilities with probabilities in the algorithm, because the features are not related to the utilities (they are external).