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POMATLABs 'fminsearch' different from Octave's 'fmincg'
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copied!<p>I am trying to get consistent answers for a simple optimization problem, between two functions in MATLAB and Octave. Here is my code:</p> <pre><code> options = optimset('MaxIter', 500 , 'Display', 'iter', 'MaxFunEvals', 1000); objFunc = @(t) lrCostFunction(t,X,y); [result1] = fminsearch(objFunc, theta, options); [result2]= fmincg (objFunc, theta, options); </code></pre> <p>(Bear in mind, that X, y, and theta are defined earlier and are correct). The problem is the following: When I run the above code in MATLAB with it using fmincg, (commend out fminsearch), I get the correct answer. </p> <p>However, if I comment out fmincg and let us run fminsearch, I get no conversion whatsoever. In fact the output looks like this:</p> <pre><code> 491 893 0.692991 reflect 492 894 0.692991 reflect 493 895 0.692991 reflect 494 896 0.692991 reflect 495 897 0.692991 reflect 496 898 0.692991 reflect 497 899 0.692991 reflect 498 900 0.692991 reflect 499 901 0.692991 reflect 500 902 0.692991 reflect Exiting: Maximum number of iterations has been exceeded - increase MaxIter option. Current function value: 0.692991 </code></pre> <p>Increasing the number of iterations doesnt do jack. In contrast, when using the fmincg, I see it converging, and it finally gives me the correct result:</p> <pre><code>Iteration 1 | Cost: 2.802128e-001 Iteration 2 | Cost: 9.454389e-002 Iteration 3 | Cost: 5.704641e-002 Iteration 4 | Cost: 4.688190e-002 Iteration 5 | Cost: 3.759021e-002 Iteration 6 | Cost: 3.522008e-002 Iteration 7 | Cost: 3.234531e-002 Iteration 8 | Cost: 3.145034e-002 Iteration 9 | Cost: 3.008919e-002 Iteration 10 | Cost: 2.994639e-002 Iteration 11 | Cost: 2.678528e-002 Iteration 12 | Cost: 2.660323e-002 Iteration 13 | Cost: 2.493301e-002 . . . Iteration 493 | Cost: 1.311466e-002 Iteration 494 | Cost: 1.311466e-002 Iteration 495 | Cost: 1.311466e-002 Iteration 496 | Cost: 1.311466e-002 Iteration 497 | Cost: 1.311466e-002 Iteration 498 | Cost: 1.311466e-002 Iteration 499 | Cost: 1.311466e-002 Iteration 500 | Cost: 1.311466e-002 </code></pre> <p>This gives the correct asnwer.</p> <p>So what gives? Why is fminsearch not working in this minimization case? </p> <p>Additional context:</p> <p>1) Octave is the language that has fmincg btw, however a quick google result also retrieves this function. My MATLAB can call either.</p> <p>2) My problem has a convex error surface, and its error surface is everywhere differentiable.</p> <p>3) I only have access to fminsearch, fminbnd (which I cant use since this problem is multivariate not univariate), so that leaves fminsearch. Thanks!</p>

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