수렴 (기계학습)

A state reached when loss values change very little or not at all with each iteration. A model converges when additional training won’t improve the model. In deep model, loss values sometimes stay constant or nearly so for many iterations before finally descending. During a long period of constant loss values, you may temporarily get a false sense of convergence.1

See also early stopping.

Footnotes

  1. developers.google.com/machine-learning/glossary#convergence

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