In the context of Artificial Neural Networks (ANN) in MATLAB, the regression plot typically shows the correlation coefficient (R), which is a measure of how well the predicted outputs from the network match the actual target values.
The coefficient of determination ( R^2 ) is the square of the correlation coefficient and provides the proportion of the variance in the dependent variable that is predictable from the independent variable(s). The value ranges from 0 to 1, where 1 indicates perfect prediction.
The difference between these coefficients are as follows:
- Correlation Factor : Measures the linear relationship between variables.
- Regression Coefficient: Refers to the coefficients in a regression equation that quantify the relationship between predictor variables and the response variable.
- Coefficient of Determination: Indicates the proportion of variance explained by the model.
Refer to the following documentation links to read about the coefficients:
- https://www.mathworks.com/help/matlab/ref/corrcoef.html#bunkanr
- https://www.mathworks.com/help/stats/coefficient-of-determination-r-squared.html
Also, refer these MATLAB answers link to better understand the regression plot for the ANN:
