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 …
The Softmax Activation Function converts a vector of numbers into a vector of probabilities that sum to 1. It's applied to a model's outputs (or …
The Sigmoid function, also known as the Logistic Function, squeezes numbers into a probability-like range between 0 and 1.^{1} Used in Binary Classification model …
When data is provided to a model that is significantly different from what it was trained on, it's referred to as out-of-domain data.