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Why log loss[-sum(log f (yis; xsi ))] is used in multi classification problem instead of cross entropy?
For example, I have three categories. When the prediction y of the network is correct, such as equal to (1,0,0) or (0,1,0), the loss is infinite.
The text was updated successfully, but these errors were encountered:
Why log loss[-sum(log f (yis; xsi ))] is used in multi classification problem instead of cross entropy?
For example, I have three categories. When the prediction y of the network is correct, such as equal to (1,0,0) or (0,1,0), the loss is infinite.
The text was updated successfully, but these errors were encountered: