Hello,
May I ask which framework are you using? OPF or Network API, from what
you've typed I guess this is Network API. I'm wondering how you made:
raw midi data -> Encoder -> Spatial Pooler -> Temporal Pooler -> CLA >
Classifier -> prediction
Also what encoder did you use? Have you followed some example codes?
Thank you
On 01/13/2016 02:47 PM, 박진만 wrote:
Hello, I'm newbie to NUPIC& NUPIC-mailing list.
I'm working on training midi files(*.mid , a sort of music file) using
low-level codes.
Low-level codes mean just a raw sp and tp code, not network API or OPF.
I prefer to use low-level codes because it's easier for me to modify the
codes.
I used a simple structure like this:
raw midi data -> Encoder -> Spatial Pooler -> Temporal Pooler -> CLA
Classifier -> prediction
The result was quit awesome. the HTM successfully predicted the whole
sequence with no error.
Then I wanted to change the structure to be hierarchical like this :
raw midi data -> Encoder -> SP1 -> TP1 -> SP2 -> TP2 -> CLA Classifier
-> prediction
but I cannot implement the structure because i don't know how the layer
1 and layer 2 is linked. I already watched "hierarchy_network_demo.py",
but the code just tells us "UniformLink".
What does the term "UniformLink" mean?
I think it's gonna be a strange architecture if TP1's output(array of
cells) becomes the input of SP2, because in this hierarchy, layer 2 (SP2
and TP2) will have bigger column dimension than those of layer 1, which
is somehow weird.
to sum up, my questions are :
1. How they are linked between layers.
2. Any hierarchy structure examples in low-level (not Network API, not OPF)
Any comments would be very helpful.
Thank you.
