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

4 次查看（过去 30 天）
Nadia A
Nadia A 2016-11-10
回答： Ahmet Cecen 2016-11-10
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?

请先登录，再回答此问题。

采纳的回答

Ahmet Cecen
Ahmet Cecen 2016-11-10
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.

更多回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Linear and Nonlinear Regression 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by