Why is the neg. log. Likelihood a commonly used loss function?
The -neg log likelihood is practical and able to archive a good generalization. It is practical because it can be used for classificstion and in a regression setting, so we do not need a spefic loss function. It archives a good Generalization because it minimizes
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