Machine Learning FAQ
What is the derivative of the logistic sigmoid function?
The derivative of the logistic sigmoid function,
\[\sigma(x) = \frac{1}{1 + e^{-x}},\]is defined as
\[\frac{d}{dx} = \frac{e^{-x}}{(1 + e^{-x})^2}.\]Let me walk through the derivation step by step below. \(\begin{align} \frac{d}{dx}\sigma(x) & = \frac{d}{dx} \frac{1}{1+e^{-x}}\\ & = \frac{d}{dx}\big( 1+ e^{-x} \big) ^{-1} \quad[\text{apply chain rule}]\\ & = -(1 + e^{-x})^{-2} \cdot \frac{d}{dx}(1+e^{-x}) \quad[\text{apply sum rule}] \\ & = -(1 + e^{-x})^{-2} \cdot \bigg(\frac{d}{dx}1 + \frac{d}{dx}e^{-x}\bigg) \\ & = -(1 + e^{-x})^{-2} \cdot \frac{d}{dx}e^{-x} \quad[\text{apply chain rule}]\\ & = -(1 + e^{-x})^{-2} \cdot e^{-x}\frac{d}{dx} (-x)\\ & = -(1 + e^{-x})^{-2} \cdot \big(- e^{-x} \big)\\ & = \frac{1}{(1 + e^{-x})^{2}} \cdot e^{-x} \\ & = \frac{e^{-x}}{(1 + e^{-x})^{2}} \end{align}\)
We can further simplify the derivative to the expression \(\sigma(x)(1-\sigma(x))\): \(\begin{align} \frac{e^{-x}}{(1 + e^{-x})^{2}} &= \frac{e^{-x}}{1 + e^{-x}}\cdot\frac{1}{1 + e^{-x}} \\ & = \frac{-1 + 1 + e^{-x}}{1 + e^{-x}}\cdot\frac{1}{1 + e^{-x}}\\ & = \bigg(\frac{-1 }{1 + e^{-x}} + \frac{1 + e^{-x} }{1 + e^{-x}} \bigg)\cdot\frac{1}{1 + e^{-x}}\\ & = \bigg(\frac{-1 }{1 + e^{-x}} + 1 \bigg)\cdot\frac{1}{1 + e^{-x}}\\ & = \bigg(1 - \frac{1 }{1 + e^{-x}} \bigg)\cdot\frac{1}{1 + e^{-x}}\\ & = \big(1-\sigma(x)\big) \cdot \sigma(x) \end{align}\)
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