computeGrad2 {TeachNet}

Computes a gradient

Description

This function computes the gradient for a two hidden layer network.

Usage

computeGrad2(x, y, I, M, H, weights, f, f_d, m_f)

Arguments

x

properties of observation

y

characteristic of observation (zero or one)

I

numbers of input neurons

M

number of neurons in first hidden layer

H

number of neurons in second hidden layer

weights

the weights with that the gradient should be computed

f

the activation function of the neural network

f_d

the derivative of the activation function

m_f

the function for the interim value m. It is two times the output of the network minus the observed characteristic.

Value

A Weights2 class with the gradient parts

Author(s)

Georg Steinbuss

See Also

Weights-class computeGrad2