You train your own set by posting the document and the classification / category to the service. The training set is then used to calculate the prior probabilities needed by Bayes theorem. Once you have a proper training set, you can post a document to the service and it will return a list of probable categories from the training set.
Your set might look something like this:
Category - Document
negative - I don't like ice cream
positive - That's an awesome idea
neutral - The wind is blowing today
positive - We won!
You'll get a categorization of either positive, negative or neutral.
Yes, well - I understand the general theory, but I don't understand how it applies to managing your bank account.
I do manage my bank account, but I don't see any need for an "classifier": when I input (or check) a supermarket bill I don't need much help in setting it to "GROCERIES".
Basically anything that gets into my accounting files it's either something I know already what is about, or else something I need to investigate (e.g.: a speed ticket from a foreign country, routed to my credit card by the car rental company).
Your set might look something like this:
Category - Document
negative - I don't like ice cream
positive - That's an awesome idea
neutral - The wind is blowing today
positive - We won!
You'll get a categorization of either positive, negative or neutral.