Table 3 Performance metrics for evaluating the proposed ML methods.

R²

\(\:1-\frac{{\sum\:}_{i}{\left({y}_{i}-{\widehat{y}}_{i}\right)}^{2}}{{\sum\:}_{i}{\left({y}_{i}-{\stackrel{-}{y}}_{i}\right)}^{2}}\)

MSE

\(\:\frac{1}{n}\sum\:_{i=1}^{n}{({y}_{i}-{\widehat{y}}_{i})}^{2}\)

RMSE

\(\:\sqrt{\frac{1}{n}\sum\:_{i=1}^{n}{({y}_{i}-{\widehat{y}}_{i})}^{2}}\)

MAE

\(\:MAE=\frac{1}{n}\sum\:_{i=1}^{n}\left|{y}_{i}-{\widehat{y}}_{i}\right|\)

MAPE

\(\:MAE=\frac{1}{n}\sum\:_{i=1}^{n}\left|\frac{{y}_{i}^{{\prime\:}}-{y}_{i}}{{y}_{i}}\right|\)