Articles tagged with MachineLearning
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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 …
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Categorical Cross-Entropy Loss
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 …
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Negative Log-Likelihood
Negative log-likelihood is a loss function used in multi-class classification.
Calculated as , where
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Softmax Activation Function
The Softmax function converts a vector of numbers into a vector of probabilities that sum to 1. It's applied to a model's outputs (or Logits …
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Sigmoid Activation Function
The Sigmoid function squeezes numbers into a probability-like range between 0 and 1.1 Used in Binary Classification model architectures to compute loss on discrete …
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Out-of-domain data
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.
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Mean Absolute Difference - L1 Loss
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 …
