Binary Cross-Entropy Loss
Binary Cross-Entropy (BCE), also known as log loss, is a loss function used in binary or multi-label machine learning training.
It's nearly identical to Negative …
Binary Cross-Entropy (BCE), also known as log loss, is a loss function used in binary or multi-label machine learning training.
It's nearly identical to Negative …
Categorical Cross-Entropy Loss Function, also known as Softmax Loss, is a loss function used in multiclass classification model training. It applies the Softmax Activation Function …
Negative log-likelihood is a loss function used in multi-class classification.
Calculated as $-log(\textbf{y})$, where $\mathbf{\text{y \u2026}}$
Mean Absolute Difference (MAE) is a function for assessing Regression predictions. It's also as L1 Loss because it takes the L1 Norm of the error …
Root mean-squared error (RMSE) is a function for assessing Regression predictions. Sometimes called L2 Error because it takes the L2 Norm of the error vector …