What is the Sigmoid Function? How it is implemented in Logistic Regression?
According to Wikipedia, the activation function of a node defines the output of that node given an input or set of inputs in terms of an artificial neural network. A standard integrated circuit can be seen as a digital network of activation functions that can be “ON” (1) or “OFF” (0), depending on the input.
There are different types of activation functions
· Binary Step · Linear · Sigmoid · Tanh · ReLU · Leaky ReLU · Parameterised ReLU· Exponential Linear Unit· Swish · Softmax
Today, we will discuss more on the common type of activation, sigmoid function.
What is the Sigmoid Function?
The sigmoid function is a mathematical function having a characteristic “S” — shaped curve, which transforms the values between the range 0 and 1. The sigmoid function also called the sigmoidal curve or logistic function. It is one of the most widely used non- linear activation function.
The mathematical expression for sigmoid:
Graph
