eelxpeng / unsuperviseddeeplearning-pytorch Goto Github PK

Thanks for posting this code. Its very helpful - and much more workable at this point than the original code.

Did you try to use any of the other data sets?

I'm specifically interested in the HAR data set. For some reason I can't achieve the same results as the paper using the pytorch code. Do you know why?

Hi!
In this line, why did you replace - (minus) with + at the end?

I am implementing this code on my biological datasets. When I run the code multiple times, it produces quite different results. The ARIs vary from 0.4 to 0.8. I find out that the pretrained model matters a lot to the results. How can I achieve robust results by getting a good pretrained model? Is the pretrained denoising autoencoder important to stacked autoencoder when the structure of the dae is not exactly the same as that of sdae?