softmax function oor Sjinees

softmax function

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Softmax函数

en
function that maps a k-element real-valued vector to a k-element categorical probability distribution
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In between blocks, a rectified linear unit (ReLU) is used as activation function, and then logits are being passed on to softmax that outputs a probability distribution over target classes.
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The loss layer specifies how the network training penalizes the deviation between the predicted and true labels and is normally the last layer in the network. Various loss functions appropriate for different tasks may be used there. Softmax loss is used for predicting a single class of K mutually exclusive classes.
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