I've trained a regression model which predicts the dependent variable from several independent variables. I noticed that there is a strong negative correlation (-0.86) between the dependent variable and the error (prediction - dependent variable). What does this imply?
While it can be caused by all predictions being similar, therefore, creating a linear relationship between the error and the dependent variable, there is also a positive correlation (0.47) between the predictions and the dependent variables.
Is there a way to reduce the errors for larger dependent variable values?