Solved – Machine Learning: Can training error and validation (testing) error be equal

Usually, the validation error is higher than training error, but are there any cases when they are equal?

  • Reason 1: the model is underfitted, i.e. it has a high bias:

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  • Reason 2: the model is near perfect.

  • Reason 3: the training set is very similar to the validation set, e.g. if some data from the validation set have leaked into the training set:

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  • Reason 4: if using a neural network, the training have been prematurely stopped:

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