I have a 2D array and I am trying to fit a curve on the data. my objective function is a polynomial function:

def objective(x, a, b, c):
    return a * x   b * x**2   c

I used curve_fit from scipy.optimize to find the suitable curve for the data. But, I need to know how much this model is good. what is the difference between actual data and estimated curve? how can I find this? dose curve_fit use mean square error to find the curve? how can I control this difference?

CodePudding user response：

You are better off using