Anomaly detection for multi features

[marty1885]

Thanks for your interest in HTM and asking on the forum.

@MAK

So it’s mean in the predict I need to define?

I’m not very familiar with the reasons API. But I do think that is the way to go. Maybe another forum member can help.

@MAK

For example if I have 10 parameters that share the 2048 bit span, and I try to predict part of them or all of them why this is changing the accuracy of the predict?

You predict all of them. A standard HTM network is composed with 2 layers. A SP, which reduces noise and unneeded information. And a TM, which predicts the next time step. Given a predicted SDR, you can ask SP to walk back it’s synapses to reconstruct the input field.

@MAK

with copmlex infrastructure I add more layers to my model, there’s something similar in the NuPIC, that give the ability to representing more complex infrastructure.

Unfortunately staking layers in NuPIC although is doable, it will not give you any extra performance in standard HTM. I (and other community members) am working on an implementation of the thousand brains theory which will allow multiple cortical columns to work together. But unlike staking CNN layers and extracting higher and higher level features, it utilizes multiple cortical columns to predicting simultaneously.