35 lines
1008 B
Matlab
35 lines
1008 B
Matlab
function [J, grad] = costFunction(theta, X, y)
|
|
%COSTFUNCTION Compute cost and gradient for logistic regression
|
|
% J = COSTFUNCTION(theta, X, y) computes the cost of using theta as the
|
|
% parameter for logistic regression and the gradient of the cost
|
|
% w.r.t. to the parameters.
|
|
|
|
% Initialize some useful values
|
|
m = length(y); % number of training examples
|
|
|
|
% You need to return the following variables correctly
|
|
J = 0;
|
|
grad = zeros(size(theta));
|
|
|
|
% ====================== YOUR CODE HERE ======================
|
|
% Instructions: Compute the cost of a particular choice of theta.
|
|
% You should set J to the cost.
|
|
% Compute the partial derivatives and set grad to the partial
|
|
% derivatives of the cost w.r.t. each parameter in theta
|
|
%
|
|
% Note: grad should have the same dimensions as theta
|
|
%
|
|
|
|
h = sigmoid(X*theta);
|
|
J = (1/m)*(-y'*log(h)-(1-y)'*log(1-h));
|
|
grad = (1/m)*X'*(sigmoid(X*theta)-y);
|
|
|
|
|
|
|
|
|
|
|
|
|
|
% =============================================================
|
|
|
|
end
|