A mathematical function used by a single neuron in a neural network to compute an output value from its inputs and pass that value to the next neuron. Common examples include the sigmoid and ReLU functions, which introduce non-linearity and enable the network to learn complex patterns. The choice of activation function significantly affects a model's learning efficiency and accuracy.

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• 2023r05 #91AI に利用されるニューラルネットワークにおける活性化関数に関する記述として，適切なものはどれか。