80 lines
2.1 KiB
Matlab
80 lines
2.1 KiB
Matlab
classdef NeuralNetworkConstants < handle
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%% Rules for automatic creation of new layers
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methods (Access = public)
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function const = CREATE_LAYER_WITH_ONE_NODE(~)
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const = 1;
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end
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function const = CREATE_LAYER_EQUAL_OUTPUT(~)
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const = 2;
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end
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function const = CREATE_LAYER_BY_ARGUMENT(~)
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const = 3;
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end
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function const = CREATE_MIRRORED_LAYER(~)
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const = 16;
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end
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end
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%% Rules for prune nodes in a layer
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methods (Access = public)
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function const = PRUNE_SINGLE_LEAST_CONTRIBUTION_NODES(~)
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const = 14;
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end
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function const = PRUNE_MULTIPLE_NODES_WITH_CONTRIBUTION_BELOW_EXPECTED(~)
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const = 15;
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end
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end
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%% Activation functions
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methods (Access = public)
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function const = ACTIVATION_FUNCTION_SIGMOID(~)
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const = 4;
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end
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function const = ACTIVATION_FUNCTION_TANH(~)
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const = 5;
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end
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function const = ACTIVATION_FUNCTION_RELU(~)
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const = 6;
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end
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function const = ACTIVATION_FUNCTION_LINEAR(~)
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const = 7;
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end
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function const = ACTIVATION_FUNCTION_SOFTMAX(~)
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const = 8;
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end
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end
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%% Activation functions and Loss functions (normally used as output activation function)
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methods (Access = public)
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function const = ACTIVATION_LOSS_FUNCTION_SIGMOID_MSE(~)
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const = 9;
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end
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function const = ACTIVATION_LOSS_FUNCTION_TANH(~)
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const = 10;
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end
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function const = ACTIVATION_LOSS_FUNCTION_RELU(~)
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const = 11;
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end
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function const = ACTIVATION_LOSS_FUNCTION_SOFTMAX_CROSS_ENTROPY(~)
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const = 12;
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end
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function const = ACTIVATION_LOSS_FUNCTION_LINEAR_CROSS_ENTROPY(~)
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const = 13;
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end
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end
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end
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