"numColumns = 12288". From 64x64 to 12288, Is it 1
dimension? and btw. this's 3 times than before. a really big one.
On Tue, 22 Sep 2015 20:33:20 -0700
Subutai Ahmad <[email protected]> wrote:
If you use increment and decrement of 0.0, you are essentially using
a
randomly initialized SpatialPooler. It turns out that such a "random
SP" is
actually pretty decent. You will get reasonable SDRs out of it.
Training
will make the SP more resistant to noise.
For MNIST the difference in test accuracy between trained and
untrained SP
is not large. However it takes a lot longer to train, so I left it
out of
the code. If you want to use a trained SP, you can try the
parameters
below. However you will need to go through the training set 3 or 4
times.
Separately, I have verified that if you train the SP, the network is
much
more robust to random noise than an untrained SP. This is different
from
the normal MNIST testing protocol.
--Subutai
numInputs = 1024
numColumns = 12288
numActiveColumnsPerInhArea = 1600
potentialPct = 0.4
globalInhibition = 1
stimulusThreshold = 0
synPermActiveInc = 0.001
synPermInactiveDec = 0.0005
synPermConnected = 0.5
minPctOverlapDutyCycles = 0.001
minPctActiveDutyCycles = 0.001
dutyCyclePeriod = 1000
maxBoost = 3
CPP SP seed = 1956
On Tue, Sep 22, 2015 at 7:55 PM, [email protected]
<[email protected]>
wrote:
Hello, Nupic
Recently, I test nupic.vision project, the result is good but I got
one
question.
As we know, the connect value between synapses will be update when
we
thain HTM newwork. How do we update the connected value depend on
two
parameters: "synPermActiveInc" and "synPermInactiveDec". am I right?
But in run_mnist_experiment.py example,these two parameters is 0.
That's
really strange. if we set these parameters to 0, how to traing? it's
i
llogical.
is anyone have any explanation or reference material about this
Experiment?
Thank You.
Cyan
------------------------------
[email protected]
