Matlab Curve Fitting Algorithm
Afficher commentaires plus anciens
I was trying to solve a surface fitting problem where I had two inputs [X1 X2] used to predict a third quantity Y that occupied the range [1,0). I initially created a very simple gradient descent script from scratch in Python. It was a traditional gradient descent with RMSE as the cost function. After playing aorund with different learning rates and starting guesses (learning along the way that the problem/solution seemed to be extrmeley sensitive to the learning rate and would easily diverge) the best result I was able to get was .05 RMSE.
I tried the matlab fit function next, with 'poly11' fit type and it found a surface with .0045 RMSE (1 order magnitude better than I achieved). It's not surprising to me that Matlab has a more sophisticated curve fitting algorithm than the rudamentary one I wrote up, but does anyone have an idea of what additional tricks fit() may be using that I'm not?
Réponse acceptée
Plus de réponses (0)
Catégories
En savoir plus sur Get Started with Curve Fitting Toolbox dans Centre d'aide et File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!