A sigmoid function is a bounded, differentiable, real function that is defined for all real input values and has a non-negative derivative at each point and exactly one 展开

Many natural processes, such as those of complex system learning curves, exhibit a progression from small beginnings that accelerates and … 展开

• Mitchell, Tom M. (1997). Machine Learning. WCB McGraw–Hill. ISBN 978-0-07-042807-2.. (NB. In particular see "Chapter 4: Artificial … 展开

In general, a sigmoid function is monotonic, and has a first derivative which is bell shaped. Conversely, the integral of any continuous, non-negative, bell-shaped function (with one local … 展开

• Logistic function $${\displaystyle f(x)={\frac {1}{1+e^{-x}}}}$$
• Hyperbolic tangent (shifted and scaled version of the logistic function, above) $${\displaystyle f(x)=\tanh x={\frac {e^{x}-e^{-x}}{e^{x}+e^{-x}}}}$$ 展开

• Step function – Linear combination of indicator functions of real intervals
• Sign function – Mathematical function returning -1, 0 or 1
• Heaviside step function – Indicator function of positive numbers 展开

• "Fitting of logistic S-curves (sigmoids) to data using SegRegA". Archived from the original on 2022-07-14. 展开