loss_binary_crossentropy: Binary Cross-Entropy Loss
In metANN: Metaheuristic and Gradient-Based Optimization for Neural Network Training and Continuous Problems
loss_binary_crossentropy R Documentation
Binary Cross-Entropy Loss
Description
Creates a binary cross-entropy loss function object.
Usage
loss_binary_crossentropy(epsilon = 1e-15)
Arguments
epsilon
A small positive numeric value used for numerical stability.
Value
An object of class "met_loss".
References
Bridle, J. S. (1990). Probabilistic Interpretation of Feedforward
Classification Network Outputs, with Relationships to Statistical Pattern
Recognition. In Neurocomputing: Algorithms, Architectures and Applications,
227–236. Springer.
Examples
loss <- loss_binary_crossentropy()
loss$fn(c(0, 1, 1), c(0.1, 0.8, 0.9))
metANN documentation built on May 16, 2026, 1:06 a.m.
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| loss_binary_crossentropy | R Documentation |
Binary Cross-Entropy Loss
Description
Creates a binary cross-entropy loss function object.
Usage
loss_binary_crossentropy(epsilon = 1e-15)
Arguments
epsilon |
A small positive numeric value used for numerical stability. |
Value
An object of class "met_loss".
References
Bridle, J. S. (1990). Probabilistic Interpretation of Feedforward Classification Network Outputs, with Relationships to Statistical Pattern Recognition. In Neurocomputing: Algorithms, Architectures and Applications, 227–236. Springer.
Examples
loss <- loss_binary_crossentropy()
loss$fn(c(0, 1, 1), c(0.1, 0.8, 0.9))
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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