From the point of view of fitness, fitness r? Above 0.8, it can be said that the fitting effect is good. r？ The closer the value is to 1, the better the fitting degree of the regression curve to the observed value; On the contrary, r? The smaller the value, the worse the fitting degree of the regression curve to the observed value.

Characteristic analysis of fitting degree;

R2 is generally between [0- 1], and the closer to 1, the better the fitting. It often happens that R2 is greater than 1, which doesn't mean that your model must be wrong. R2 is used to calculate the goodness of fit of linear regression model. When R2 formula of linear regression is used to calculate the fitting of nonlinear regression model, R2 may be greater than 1. R refers to the statistical index closely related to the response variables. According to the different characteristics of related phenomena, the names of their statistical indicators are also different.