Sigmoid
Sigmoid function is a mathematical function having a characteristic "S"-shaped curve or sigmoid curve. A common example of a sigmoid function is the logistic function.
Definition[edit | edit source]
In general, a sigmoid function is real-valued and differentiable, having either a non-negative or non-positive first derivative which is bell shaped. There are also many other differential equations which have sigmoid solution.
Examples[edit | edit source]
There are many known sigmoid functions such as the Logistic function, Hyperbolic tangent, Arctangent, Error function, Generalised logistic function, Smoothstep, Gudermannian function, Algebraic sigmoid function, and Hill equation.
Uses[edit | edit source]
Sigmoid functions are often used in Artificial neural networks to introduce nonlinearity in the model. They are also used in Machine learning algorithms to map predictions to probabilities.
See also[edit | edit source]
- Logistic regression
- Logistic function
- Activation function
- Softmax function
- Rectifier (neural networks)
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Contributors: Prab R. Tumpati, MD