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Running Start/CSB320 - Machine Learning Concepts/Class 4-23 (Model Validation & Evaluation).md

@@ -84,4 +84,4 @@ Logistic regressions also only predict between 0 - 1 (probabilities) so any erro
 The log loss function is used to penalize wrong predictions more harshly when they are more confident.
 
 ![[LogLoss.excalidraw]]
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+Only one of the terms inside of the parentheses will be non-zero based on if the observed class is 0 or 1. The log loss function then penalizes the incorrect prediction much more heavily the closer it is to the incorrect value