Responsive Ad Area

Share This Post

test

Is softmax used when only the most probable class will be used?

I have a deep learning classification problem with 17 classes and I am working in Pytorch. The architecture includes the crossEntropy loss, implemented after a linear layer.

I believe that, normally, one computes a softmax activation and interprets as probablity for the corresponding output classes. But softmax is a monotonic function and it seems that, if I just want the most probable class, I can simply choose the class with the maximum score after the linear layer, leaving the softmax out.

Given that softmax is the default, widely used activation in classification problems, I wonder if I am missing something important here. Can anyone guide me?

Note that I have googled a large number of sites but, as far as I could understand, none answering this basic question (although there was a lot of information that was provided).

Thanks


Is softmax used when only the most probable class will be used?
Is softmax used when only the most probable class will be used?
test
{$excerpt:n}

Share This Post

Leave a Reply

Your email address will not be Publishedd. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>

Skip to toolbar