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NeuralNetworkConstants.m
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% Marcus Vinicius Sousa Leite de Carvalho
% marcus.decarvalho@ntu.edu.sg
%
% NANYANG TECHNOLOGICAL UNIVERSITY - NTUITIVE PTE LTD Dual License Agreement
% Non-Commercial Use Only
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% Copyright (c) 2019
% Marcus Vinicius Sousa Leite de Carvalho
% marcus.decarvalho@ntu.edu.sg
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classdef NeuralNetworkConstants < handle
%% Rules for automatic creation of new layers
methods (Access = public)
function const = CREATE_LAYER_WITH_ONE_NODE(~)
const = 1;
end
function const = CREATE_LAYER_EQUAL_OUTPUT(~)
const = 2;
end
function const = CREATE_LAYER_BY_ARGUMENT(~)
const = 3;
end
function const = CREATE_MIRRORED_LAYER(~)
const = 16;
end
end
%% Rules for prune nodes in a layer
methods (Access = public)
function const = PRUNE_SINGLE_LEAST_CONTRIBUTION_NODES(~)
const = 14;
end
function const = PRUNE_MULTIPLE_NODES_WITH_CONTRIBUTION_BELOW_EXPECTED(~)
const = 15;
end
end
%% Activation functions
methods (Access = public)
function const = ACTIVATION_FUNCTION_SIGMOID(~)
const = 4;
end
function const = ACTIVATION_FUNCTION_TANH(~)
const = 5;
end
function const = ACTIVATION_FUNCTION_RELU(~)
const = 6;
end
function const = ACTIVATION_FUNCTION_LINEAR(~)
const = 7;
end
function const = ACTIVATION_FUNCTION_SOFTMAX(~)
const = 8;
end
end
%% Activation functions and Loss functions (normally used as output activation function)
methods (Access = public)
function const = ACTIVATION_LOSS_FUNCTION_SIGMOID_MSE(~)
const = 9;
end
function const = ACTIVATION_LOSS_FUNCTION_TANH(~)
const = 10;
end
function const = ACTIVATION_LOSS_FUNCTION_RELU(~)
const = 11;
end
function const = ACTIVATION_LOSS_FUNCTION_SOFTMAX_CROSS_ENTROPY(~)
const = 12;
end
function const = ACTIVATION_LOSS_FUNCTION_LINEAR_CROSS_ENTROPY(~)
const = 13;
end
end
end