Hi,
I’m looking for the best loss function to use for blockmodeling, where I need the trained output to be compared to an ideal blockmodel.
As a toy example, if my output is a 4 x 4 matrix (say, of decimals), e.g.
0.6868  0.4088  0.3600  0.5119
0.8085  0.8537  0.7839  0.8735
0.8971  0.9433  0.5701  0.6651
0.1267  0.7847  0.7456  0.5535
[torch.FloatTensor of size 4x4]
and I need to compare this to the following blockmodel:
1  1  0  0
1  1  0  0
0  0  1  1
0  0  1  1
[torch.FloatTensor of size 4x4]
What loss function would I use?
If there is no suitable loss function in PyTorch at present, what’s the name of a suitable loss function from other papers/sources/packages that I could explore and try to code into my own custom loss function in PyTorch?
Thank you for help.