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### In which cases is the categorical cross-entropy better than the mean squared error?

As a rule of thumb, mean squared error (MSE) is more appropriate for regression problems, that is, problems where the output is a numerical value (i.e. a floating-point number or, in general, a real ...
• 37.1k
Accepted

### Why are there two versions of softmax cross entropy? Which one to use in what situation?

It's the same thing, first version is the special case of the more general one. In the first case you only have two classes, it's binary cross-entropy, and they also included iteration over batch of ...
• 2,286

• 37.1k
1 vote
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### How should I penalize the model proportionally to the error?

I want to make it so that if the correct label is 3, then it will penalize the model less heavily if it classifies a 4 than a 7 because 4 is closer numerically to 3 than 7 is. How do I do this? ...
• 26.6k

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