The option "Evaluate all states" allows to carry out the targeted evaluation for each state of your variable. Obviously, if you are only interested in the confusion matrix and its related metrics, this is not useful as it's not changing. However, the Gains, Lift, Roc, Calibration curves are state specific.The maximum set of evidence is for evaluation the quality of your model in the context of an Adaptive Questionnaire, where you are not using all the variables for the computation of the posterior, but only the n most informative variables.The uniform posterior is usually generated when the observation you are using are not compatible with your network (i.e. you've learned a deterministic relation that is only true in your training set). To prevent this problem, you have to use a non-informative prior when learning your model, by using the option "Edit | Edit Smooth Probability Estimation". This will add 1 (default value) virtual occurence in your database, spread uniformly across your joint probability distribution, defining then that everything is possible.