neural_network.activation_functions.exponential_linear_unit

Implements the Exponential Linear Unit or ELU function.

The function takes a vector of K real numbers and a real number alpha as input and then applies the ELU function to each element of the vector.

Script inspired from its corresponding Wikipedia article https://en.wikipedia.org/wiki/Rectifier_(neural_networks)

Functions

exponential_linear_unit(→ numpy.ndarray)

Implements the ELU activation function.

Module Contents

neural_network.activation_functions.exponential_linear_unit.exponential_linear_unit(vector: numpy.ndarray, alpha: float) → numpy.ndarray

Implements the ELU activation function. Parameters:

vector: the array containing input of elu activation alpha: hyper-parameter

return: elu (np.array): The input numpy array after applying elu.

Mathematically, f(x) = x, x>0 else (alpha * (e^x -1)), x<=0, alpha >=0

Examples: >>> exponential_linear_unit(vector=np.array([2.3,0.6,-2,-3.8]), alpha=0.3) array([ 2.3 , 0.6 , -0.25939942, -0.29328877])

>>> exponential_linear_unit(vector=np.array([-9.2,-0.3,0.45,-4.56]), alpha=0.067)
array([-0.06699323, -0.01736518,  0.45      , -0.06629904])