Table 4 Overview of assessment measures for regression analysis.
Metric | Equation |
|---|---|
Mean absolute error (MAE) | \(\frac{1}{{\text{n}}}\mathop \sum \nolimits_{{{\text{i}} = 1}}^{{\text{n}}} \left| {\text{y}_{\text{i}} - \hat{\text{y}}_{\text{i}} } \right|\) |
Mean squared error (MSE) | \(\frac{1}{{\text{n}}}\mathop \sum \nolimits_{{{\text{i}} = 1}}^{{\text{n}}} \left( {\text{y}_{\text{i}} - \hat{\text{y}}_{\text{i}} } \right)^{2}\) |
Root mean squared error (RMSE) | \(\sqrt {\frac{1}{{\text{n}}}\mathop \sum \nolimits_{{{\text{i}} = 1}}^{{\text{n}}} \left( {\text{y}_{\text{i}} - \hat{\text{y}}_{\text{i}} } \right)^{2} }\) |
R-square | \(1 - \frac{{\mathop \sum \nolimits_{{{\text{i}} = 1}}^{{\text{N}}} \left( {\text{y}_{\text{i}} - \hat{\text{y}}_{\text{i}} } \right)^{2} }}{{\mathop \sum \nolimits_{{{\text{i}} = 1}}^{{\text{N}}} \left( {\text{y}_{\text{i}} - \hat{\text{y}}_{\text{i}} } \right)^{2} }}\) |
Variance score | \(1 - \frac{{Var\left( {y - \hat{y}} \right)}}{Var\left( y \right)}\) |
