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How to reduce the rmse for a fit obtained using curve fitting toolbox

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Nadia A
Nadia A on 10 Nov 2016
Answered: Ahmet Cecen on 10 Nov 2016
Hi I need to find a function which best fits x and y data points as given below
xdata=[0.500000000000000,0.700000000000000,1];
ydata=[7862.13480751439,5801.18185697929,4993.13280898239];
When I use Curve fitting toolbox, it returns a polynomial function with the goodness of fit as given below
Linear model Poly2:
f(x) = p1*x^2 + p2*x + p3
Coefficients:
p1 = 1.522e+04
p2 = -2.857e+04
p3 = 1.834e+04
Goodness of fit:
SSE: 1.414e-22
R-square: 1
Adjusted R-square: NaN
RMSE: NaN
ydata points appears to coincide the curve in the plot and also the sse and Rsquare are desirable but the rmse returned by the goodness of fit is NaN. Can this rmse be negelected? How is Adjusted R-square value calculated?

Accepted Answer

Ahmet Cecen
Ahmet Cecen on 10 Nov 2016
Read up on the concepts of Overfitting, Underfitting, Variance and Regression. You are fitting a function of 3 variables to 3 data points. I would say a regression problem with 3 data points is fairly meaningless to begin with, but if you have to do it, fit a line instead.

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