How backpropagation work? about bindsnet

[rafaelblevin821]

Hello, my input data is a two-dimensional matrix. Why doesn’t the loss value change significantly when I use BindsNet for regression problem research? What should I pay attention to in order to solve this problem? Thank you!

You are talking about backpropagation, loss, and regression. None of these are used in the supervised_mnist script.

[Hananel-Hazan]

Using the supervise_mnist.py script, you should pay attention to how the input is been encoded, what is the strength of the teaching signal and how much spiking activity exists in all the three layers.

[Hananel-Hazan]

This question is more relevant to the discussion section, as you have not reported any issues with BindsNET code. Backpropagation is not used in supervise_mnist.py because the algorithm uses guided STDP to train the network, changing the weights accordingly.

[Whale-xh]

Hello, my input data is a two-dimensional matrix. Why doesn’t the loss value change significantly when I use BindsNet for regression problem research? What should I pay attention to in order to solve this problem? Thank you!

[Whale-xh]

Hello, may I ask What are the functions of the variables' choice ',' clamp 'in the supervised_ mnist. py file, and' clamp 'in the run statement? What is the purpose of this setting?

[Hananel-Hazan]

Those features used to guide (supervised) the training process to depress or straighten the right weights