batch_normalization: Batch Normalization Function that normalizes the input before...

In deeplearning: An Implementation of Deep Neural Network for Regression and Classification

Description

This function normalizes the distribution of inputs to hidden layers in a neural network

Usage

batch_normalization(x, gamma, beta, mu = NULL, sigma_2 = NULL,
  epsilon = exp(-12))

Arguments

x	weighted sum of outputs from the previous layer
gamma	the gamma coefficient
beta	the beta coefficient
mu	the mean of the input neurons. If NULL, it will be caluclated in the function.
sigma_2	the variance of the input nerurons. If NULL, it will be calcualted in the function.
epsilon	a constant added to the variance for numerical stability

References

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe, Christian Szegedy

See Also

http://jmlr.org/proceedings/papers/v37/ioffe15.pdf Pg 4

deeplearning documentation built on Jan. 15, 2017, 9:52 a.m.