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Scaling
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{ None, Z-Score, Min-Max Scaling }
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Training algorithm
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{ SGD, AdaGrad, RMSProp, Adam }
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Activation function
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{ Sigmoid, ReLU, tanh, linear (in the output layer) }
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Hours of input data
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{ 24 × 3, 24 × 5, 24 × 7, 24 × 9 }
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Learning rate
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{lrd×10−1,lrd,lrd×101,lrd×102} with (lrd) = default learning rate of the
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corresponding optimiser as implemented in the python keras api
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Hidden layers
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{1,2,3,4}
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Decay
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{0,0.0001,0.001,0.01}
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Patience of early stopping
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{10,20,30}
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Test split
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{0.25,0.3,0.35}
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L2−Regularisation
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λ∈{ 0, 0.001, 0.01, 0.1} |
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Dropout
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{ 0.1, 0.2, 0.3 }
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