Softmax function
Function that maps a k-element real-valued vector to a k-element categorical probability distribution
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. It is a generalization of the logistic function to multiple dimensions, and is used in multinomial logistic regression.
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Softmax function
Function that maps a k-element real-valued vector to a k-element categorical probability distribution
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. It is a generalization of the logistic function to multiple dimensions, and is used in multinomial logistic regression.
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From Wikipedia
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. It is a generalization of the logistic function to multiple dimensions, and is used in multinomial logistic regression. The softmax function is often used as the last activation function of a neural network to normalize the output of a network to a probability distribution over predicted output classes.
Text: Wikipédia, CC BY-SA 4.0. · Image: Fschwarzentruber (CC BY-SA 4.0) ·
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