Squared Error Loss Function

A Squared Error Loss Function is a loss function that is a squared error function.

• Example(s):
  • One-half Squared-Error Cost Function,
  • …
• Counter-Example(s):
  • Log Loss.
• See: Squared Error, Mean Squared Error, Square Loss Function, Squared Error Function, Cross-Entropy Measure, Mean Absolute Error, Mean Squared Error, Learning Cost Function.

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References

2014

• (Wikipedia, 2014) ⇒ http://en.wikipedia.org/wiki/Mean_squared_error#Loss_function
  • Squared error loss is one of the most widely used loss functions in statistics, though its widespread use stems more from mathematical convenience than considerations of actual loss in applications. Carl Friedrich Gauss, who introduced the use of mean squared error, was aware of its arbitrariness and was in agreement with objections to it on these grounds. The mathematical benefits of mean squared error are particularly evident in its use at analyzing the performance of linear regression, as it allows one to partition the variation in a dataset into variation explained by the model and variation explained by randomness.

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