On 5/3/11 5:05 PM, Jason Baldridge wrote:
Sure. But that proposal will involve blasting things apart. ;)
What do you think about defining some kind of training attribute file,
which specifies all the parameters which are needed to train a model.
This file could contain the training algorithm combined with several
attributes,
e.g. cutoff, iterations, etc. The attributes could also be algorithm
dependent,
e.g for Perceptron there could be a property which defines the number of
iterations
where the accuracy must be identical in order to stop.
Such a file would make our code simpler in some places, e.g command line
argument
handling, writing of these attributes in to the model packages, simple
APIs for training
with all kind of parameters, etc.
Any opinions?
Jörn
