The default feature (the prior feature) produced by the prior feature
generator
is the same for every context and can be used to measure the
distribution of the outcomes in the training data.
Some outcomes are usually much more frequent than others, depending on
the task,
e.g. in the tokenizer NO_SPLIT is much more common than SPLIT.
HTH,
Jörn
On 12/11/2012 01:07 PM, Jim foo.bar wrote:
I've asked a couple of times before but I got no answer! Jorn replied
to me at some point but his response was very brief and confused me
even more!
I'm begging you!!! I'm writing a paper for BMC bioinformatics and I
cannot explain this feature properly! I'm struggling to find
information on the web...
PLEASE, PLEASE, PLEASE, devote 5 minutes to explain what this feature
does and how it works. An example would be awesome...
thanks in advance...
Jim
