Quality of predictions
In a “perfect” predictive model
predicted value
==actual value
of the variable for every observation.We want the predictions to be reasonably close to the actual values.
To quantify the quality of predictions we can use the difference between the
predicted value
and theactual value
called as residual.
For a continuous dependent variable \(Y\), residual \(r_i\) for the \(i\)-th observation in a dataset:
\[\begin{equation} r_i = y_i - f(\underline{x}_i) = y_i - \widehat{y}_i \end{equation}\]