Can RRL be used for regression?

[KongMingxi]

Hi authors,

Thanks for this great work! I think it is very helpful for data analysis.
I wonder if it can be used for regression and how to perform that?

Best,

Mx

[12wang3]

Hi KongMingxi,

RRL can be used for regression because the last layer is a linear layer (FC layer). To do regression, you just need to change the loss function, i.e., delete the softmax and use the loss function designed for regression. It should be noted that you need to calculate $\frac{\partial Loss()}{\partial \bar{Y}}$ like the following code:

rrl/rrl/models.py

Line 179 in 656098b

y_pred_mllp.backward((y_prob - y) / y.shape[0]) # for CrossEntropy Loss

What's more, the regression performance of RRL is not verified by experiments, so I'm not sure if RRL can get a good result.

[KongMingxi]

Many thanks for your reply!