Softmax Vs Logistic Vs Sigmoid

Published: 10 Dec 2015 Category: deep_learning

Softmax

$\sigma(x) = \frac{1} {1 + exp^{-x}}$ $\frac{d\sigma(x)} {dx} = (1 - \sigma(x)) * \sigma(x)$

Logistic

Sigmoid

$y_i = \frac{e^{\zeta_i}} {\sum_{j \in L} e^{\zeta_j}}$

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