The softmax function, also known as softargmax or the normalized exponential function, converts a tuple of real numbers into a probability distribution over that many possible outcomes. It is a generalization of the logistic function to multiple dimensions and is used in multinomial logistic regression, and it is commonly used as the final activation function of a neural network so that the network raw outputs are normalized into a probability distribution over the predicted output classes. This description is adapted from Wikipedia contributors under CC BY-SA 4.0; changes were made. https://creativecommons.org/licenses/by-sa/4.0/
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1. Softmax Function (Wikipedia)
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The softmax function, also known as softargmax or normalized exponential function, converts a tuple of K real numbers into a probability distribution over K possible outcomes.
Wolfram MathWorld: Softmax Function
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Applied Mathematics Optimization
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