IDLmlafGaussian

An activation function is a mathematical tool used in machine learning to impart non-linearities into linear systems. Choosing the proper activation function(s) is an important step in designing your neural network. The IDLmlafGaussian activation function is implemented with the following formula:

Example

Compile_opt idl2

Data = findgen(10)

actFunc = IDLmlafGaussian()

Print, actFunc(data)

Syntax

actFunc = IDLmlafGaussian()

Result = actFunc(X [, GRADIENT=value])

Note: IDL activation functions work by overloading the function operator. To avoid compilation problems, make sure that every routine that uses an activation function contains the statement:

Compile_opt idl2

Arguments

None

Keywords

GRADIENT (optional)

Set this keyword to a named variable to receive the gradient of the activation function at each point in the input X array. The output gradient will have the same dimensions as the input X array.

Version History

8.7.1

Introduced