Mercurial > hg > machine-learning-hw2
view costFunction.m @ 5:a4c4da8f4ac0
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author | Jordi Gutiérrez Hermoso <jordigh@octave.org> |
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date | Tue, 08 Nov 2011 00:56:18 -0500 |
parents | 8b902ada47e9 |
children | 141d81a2acf5 |
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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. m = length (y); ## h_theta(x) ht = sigmoid (X*theta); J = -sum (y.*log (ht) + (1 - y).*log (1 - ht))/m grad = X'*(ht - y)/m; endfunction