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B

back(Matrix) - Method in interface com.jml.neural_network.activations.ActivationFunction
Applies backward pass of the activation function to a matrix (i.e.
back(Matrix) - Method in class com.jml.neural_network.activations.Linear
Applies the derivative of the activation function, element-wise, to a matrix.
back(Matrix) - Method in class com.jml.neural_network.activations.Relu
Applies the derivative of the ReLU activation function to a matrix element-wise.
back(Matrix) - Method in class com.jml.neural_network.activations.Sigmoid
Applies the derivative of the sigmoid activation function element-wise to a matrix.
back(Matrix) - Method in class com.jml.neural_network.activations.Softmax
Applies the derivative of the activation function, element-wise, to a matrix.
back(Matrix) - Method in class com.jml.neural_network.activations.Tanh
Applies the derivative of the activation function, element-wise, to a matrix.
back(Matrix) - Method in interface com.jml.neural_network.layers.BaseLayer
Computes backward pass for layer.
back(Matrix) - Method in class com.jml.neural_network.layers.Dense
Computes the backward pass for this layer.
back(Matrix) - Method in class com.jml.neural_network.layers.Dropout
 
back(Matrix) - Method in class com.jml.neural_network.layers.Linear
Computes backward pass for layer.
BaseLayer - Interface in com.jml.neural_network.layers
Base layer interface.
BIAS - Enum constant in enum class com.jml.neural_network.ModelTags
 
binCrossEntropy - Static variable in class com.jml.losses.LossFunctions
The binary cross-entropy loss function.
Block - Class in com.jml.core
Blocks are used to define a model.
Block(String, String) - Constructor for class com.jml.core.Block
Constructs a block with specified name and content.
buildFileContent(Block...) - Static method in class com.jml.core.Block
Builds the content of a markup file containing blocks.
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