Thank you for taking the time to read this question! Is it possible to create a Naive Bayes classifier from the prior probabilities? I do not have a training set per se, and I was hoping to not include the correct outcome in the data. So, I was hoping to predict the outcome from the prior probabilities, not from a training set. Can this be done in RapidMiner?
On a related note, is it possible to include the prior probabilities of the outcomes? If, for example, I know that 80% of the outcomes will be of one type and the remaining 20% will be the other, is it possible to enter this into the program?
What you want is probably not possible. RapidMiner usually needs training data to create any kind of model. Maybe you can create a rule-based process with the Branch operator or the Generate Attributes operator, but that will be a bit tedious.