Log Loss

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Glossary

Log Loss

Log Loss, oder logarithmischer/Cross-Entropy-Loss, ist eine wichtige Kennzahl zur Bewertung der Leistung von Machine-Learning-Modellen – insbesondere für binäre Klassifikation – indem sie die Abweichung zwischen vorhergesagten Wahrscheinlichkeiten und tatsächlichen Ergebnissen misst und falsche oder übermäßig selbstsichere Vorhersagen bestraft.

Log Loss Machine Learning Classification +2
• 5 min read

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