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Hi,i'm Using Caps-Net to Handle High-dimensional and Small-sample Problems, but train cannot converge。My data dimension is 6670, 2 classes. what should i do ,thanks a lot
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Can you please elaborate your problem of high dimensionality and small-sample?
From what I got is that you want to know that how to converge training accuracy when input data's dimension is as big as 6670. Also do you have lesser training samples for each class? If yes, how much is it? Also if you could elaborate your network that you are currently using.
Hi,i'm Using Caps-Net to Handle High-dimensional and Small-sample Problems, but train cannot converge。My data dimension is 6670, 2 classes. what should i do ,thanks a lot
The text was updated successfully, but these errors were encountered: