[jrgnsd]

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.

[Pamar]

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).