week 5

Página 1

cost function for neural networks:

input layer : hidden layer : output unit

L = total number of layers in network

sl = no of units in layer l;

binary classification : 0 or 1; Sl = 1 ; K =1 ;

multi-class classification : K classes ; Sl = K ; Kl >=3

[1 0 0 0] ' [0 1 0 0]' [0 0 1 0]' [0 0 0 1]'

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J(theta)

Página 2

back propagation algoritm is used in neural networks to minimize the cost function J(theta) in neural networks;

(equivalent of gradient descent in logistic/linear regression)

ie., find theta such that the cost function J is a minimum;