Skip to main content

Table 2 Mathematical equations used to calculate statistical validation metrics

From: Machine learning-driven prediction of medical expenses in triple-vessel PCI patients using feature selection

Metrics

Equations

MAE

Mean absolute error

\(\frac{1}{x}\sum\limits_{i=1}^{x}|({a}^{i}-{b}^{i})|\)

MSE

Mean square error

\(\frac{1}{x}\sum\limits_{i=1}^{x}|{({a}^{i}-{b}^{i})}^{2}|\)

RMSE

Root mean square error

\(\sqrt{\frac{1}{x}\sum\limits_{i=1}^{x}{({a}^{i}-{b}^{i})}^{2}}\)

RSE

Relative Squared Error

\(\frac{\sum_{i=1}^{x}{({b}^{i}-{a}^{i})}^{2}}{\sum_{i=1}^{x}{({b}^{i}-\overline{b })}^{2}}\)

MAPE

Mean absolute percentage error

\(\frac{100\%}{x}\sum\limits_{i=1}^{x}(|\frac{{a}^{i}-{b}^{i}}{{b}^{i}}|)\)

SMAPE

Symmetric Mean Absolute Percentage Error

\(\frac{100\%}{x}\sum\limits_{i=1}^{x}(|\frac{{\widehat{|a}}_{i}-{b}^{i}|}{{\widehat{|a}}_{i}\left|+{|b}^{i}\right|/2}|)\)

MASE

Mean absolute scaled error

\(\frac{1}{x}\sum\limits_{i=1}^{x}\frac{|{a}^{i}-{b}^{i}|}{\frac{1}{n-1}\sum_{i=2}^{x}|{a}^{i}-{b}^{i}|}\)