Classification: NPL Management Ltd - Commercial
Hi,
I was wondering if someone could answer some questions I have about
swarming?
In the "rec_centre_hourly_model_params.py" file (using the hotgym
tutorial as an example) outputted after a swarm what do the parameters
it produces mean? What are they used for? And why are they important?
Also, without looking into the algorithms, what sort of calculations is
the swarm making? I understand It goes through the input data and goes
through different models and an optimization process (PSO) where it
analyses which model best suits the dataset. I also understand that the
swarm finishes when the error score no longer decreases, but how do you
generate the error score? What are the technical differences between the
different swarm sizes? Again, I know a bit about it but an explanation
would be great.
In particular, I would be very grateful if someone could explain what
the following parameters within the model_params.py file represent:
'clParams': { 'alpha':
'_classifierInput': {'n':
'spParams':{ 'synPermInactiveDec':
'tpParams': { 'activationThreshold':
'tpParams': { 'minThreshold':
'tpParams': { 'pamLength':
I have just been watching the following video and found it very helpful
but I still have some questions.
https://www.youtube.com/watch?v=xYPKjKQ4YZ0
Apologies if these questions have already been asked before, link me to
a feed if so.
Thanks in advance,
Cavan
Mr Cavan Day-Lewis
Vacation Student
National Physical Laboratory
Hampton Rd | Teddington | Middlesex | UK | TW11 0LW
t: 020 8943 XXXX
e: [email protected]
w: www.npl.co.uk
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