Compute the gradient for regularized logistic regression
This commit is contained in:
parent
f391ac661e
commit
9e9b9990bb
1 changed files with 4 additions and 0 deletions
|
@ -20,6 +20,10 @@ grad = zeros(size(theta));
|
||||||
J = 1/m * (-y'*log(sigmoid(X*theta)) - (1-y)'*log(1-sigmoid(X*theta))) ...
|
J = 1/m * (-y'*log(sigmoid(X*theta)) - (1-y)'*log(1-sigmoid(X*theta))) ...
|
||||||
+ lambda/(2*m) * theta(2:end)' * theta(2:end);
|
+ lambda/(2*m) * theta(2:end)' * theta(2:end);
|
||||||
|
|
||||||
|
regularization_term = ...
|
||||||
|
lambda/m * (theta .* prepad(ones(length(theta)-1, 1), length(theta), 0));
|
||||||
|
grad = 1/m * X' * (sigmoid(X*theta) - y) + regularization_term;
|
||||||
|
|
||||||
% =============================================================
|
% =============================================================
|
||||||
|
|
||||||
end
|
end
|
||||||
|
|
Reference in a new issue