GLOSSARY TERM
What is Cross-Entropy Loss?
A primary loss function used for training classification models.
Cross-entropy loss measures the performance of a classification model whose output is a probability value between 0 and 1. It heavily penalizes confident but incorrect predictions, driving the model toward the true underlying distribution.
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