Types of Loss Function

Loss function is an important part in artificial neural networks, which is used to measure the inconsistency between predicted value (^y) and actual label (y). It is a non-negative value, where the robustness of model increases along with the decrease of the value of loss function.

Read this article to see the various types of loss functions

Some of the loss functions are:

  • mean squared error
  • mean absolute error
  • mean absolute percentage error
  • mean squared logarithmic error
  • kullback leibler divergence

See the article for the full list
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