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This brief readme is designed to help you get started with using the Reverend training and testing UI. This is how I use the trainer. I first prepare a couple of directories full of email. One will have a mix of all kinds of email that I want to classify and one for testing that is, say, containing only spam files. I type: python emailtrainer.py I click on the 'New Pool' button and create a pool for each category or bucket that I want to classify the data into. e.g. 'Clean' and 'Spam'. I use the radio buttons to classify the emails. I page back and forth to make sure that new training does not undo old training. Once I am happy with the training. I click 'Save' to save the Reverend data. I can load it later and continue training. When I want to test, I load the Reverend data using the 'Load' button. I then click on the 'Testing' button on the left. I click 'Run Test' which brings up the first of 2 dialogs, asking me to select the test data, e.g. my directory full of spam. The next dialog asks for the correct answer to this set of messages. I type in 'Spam' (case must match your pool name). I have lots of improvements in mind from training reinforcement to better testing and analysis. The trainer is designed to be data-agnostic. Look at example/emailtrainer.py to see how you can simply wrap your domain objects and make them place nice with the UI. Enjoy, -A-