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