Long answer: When it tries to serialize the "bucket" object, it also needs to
serialize all of the models in the bucket. By design, however, only the best
model in the bucket for your problem is actually trained, so it failed when it
tried to serialize the other models that had not been trained. In this case,
"not trained yet" is the message reported by the decisiontree class when it is
serialized, but has not been trained. This means that the "meanmarginstree"
model must be getting better accuracy with your data. So, for now, a simple
work-around is to use "bag 16 meanmarginstree end" as your model. It should
obtain the same accuracy with your data since the decisiontree is apparently
just dead weight. Another solution is to get the latest source code. (See htt
p://waffles.sourceforge.net/tutorial/subversion.html) Thanks for catching this bug.
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
Why I get "not trained yet" message, and usage text to this command:
waffles_learn train my.arff -labels 3 -ignore 0-2,4-5,24 bag 16 bucket
decisiontree meanmarginstree end end
?
Short answer: This was a bug. I just fixed it.
Long answer: When it tries to serialize the "bucket" object, it also needs to
serialize all of the models in the bucket. By design, however, only the best
model in the bucket for your problem is actually trained, so it failed when it
tried to serialize the other models that had not been trained. In this case,
"not trained yet" is the message reported by the decisiontree class when it is
serialized, but has not been trained. This means that the "meanmarginstree"
model must be getting better accuracy with your data. So, for now, a simple
work-around is to use "bag 16 meanmarginstree end" as your model. It should
obtain the same accuracy with your data since the decisiontree is apparently
just dead weight. Another solution is to get the latest source code. (See htt
p://waffles.sourceforge.net/tutorial/subversion.html) Thanks for catching this bug.