hi everyone,
I am new to CLA and nupic and I have some troubles in getting started,
understand how to build a model and set the parameters correctly.
my questions:
1) Is there a tutorial or a reasoned example (i.e. highlighting the main
implementation/options choices.) where i can start from? for now I have
started reading the examples and going up in the "hierarchy", trying to
understand the source code documentation...but it's almost a reverse
engineering approach :). I have found the slides of the oscon lecture...is
there also a video?
2) I have found the description_template.py but it seems to me that has a
quite different syntax respect to the others description files (e.g. the
encoders). am i missing something?
3) in the scalar_1 example:
the randomData feature is ignored, isn't it? how the "n" and "w" are
chosen? is there a rule?
why is the SP disabled?
i have tried to change this example to classify the patterns according
to the sum of two features, i.e.
class, field1, field2, randomData
float,float,float,float
,,,
3,1,2, something
7,3,4, something
7,1,6, something
1,0,1, something
5,1,4, something
....
.....
to do this i've just added an encoder for field2 and randomData...but i
am unable to get a decent result. where i am wrong?
4) is there a way to save the model produced and use it again both to make
inferences and to do some more train over new data?
As what concerning the latter i have hacked the OpfRunExperiment.py
file with a for cycle
model=runExperiment(sys.argv[1:])
for c in range (0,9):
runExperiment(sys.argv[1:],model)
but i am quite sure that there is a cleaner and smarter way of doing
this
thanks
Alessandro
p.s. sorry for my bad english
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