一段时间以来,我一直在尝试在 matlab 中实现逻辑回归。我已经这样做了,但由于我不知道的原因,我无法使用 fminunc 执行单次迭代。当它调用函数时,程序只是无限期地进入等待模式。代码有问题,还是我的数据集很大?
function [theta J] = logisticReg(initial_theta, X, y, lambda, iter)
% Set Options
options = optimset('GradObj', 'on', 'MaxIter', iter);
% Optimize
[theta, J, exit_flag] = fminunc(@(t)(costFunctionReg(t, X, y, lambda)), initial_theta, options);
end
在哪里
X is a [676,6251] matrix
y is a [676,1] vector
lambda = 1
initial_theta is [6251, 1] vector of zeros
iter = 1
任何“指向正确的方向”将不胜感激!PS,我能够运行 costFunctionReg。所以我假设它是这个功能。
根据要求,costFunctionReg
function [J, grad] = costFunctionReg(theta, X, y, lambda)
m = length(y); % number of training examples
J = 0;
grad = zeros(size(theta));
hyp = sigmoid(X * theta);
cost_reg = (lambda / (2*m)) * sum(theta(2:end).^2);
J = 1/m * sum((-y .* log(hyp)) - ((1-y) .* log(1-hyp))) + cost_reg;
grad(1) = 1/m * sum((hyp - y)' * X(:,1));
grad(2:end) = (1/m * ((hyp - y)' * X(:,2:end))) + (lambda/m)*theta(2:end)';
回答@Rasman 问题:
Cost at initial theta: NaN
press any key to continue
Performing Logistic Regrestion
Error using sfminbx (line 28)
Objective function is undefined at initial point. fminunc cannot continue.
Error in fminunc (line 406)
[x,FVAL,~,EXITFLAG,OUTPUT,GRAD,HESSIAN] = sfminbx(funfcn,x,l,u, ...
Error in logisticReg (line 8)
[theta, J, exit_flag] = fminunc(@(t)(costFunctionReg(t, X, y, lambda)),
initial_theta, options);
Error in main (line 40)
[theta J] = logisticReg(initial_theta, X, y, lambda, iter);
第一行是我使用 initial_theta 运行 costFunctionReg。