A machine learning-based algorithm used to estimate the physiological elongation of ocular axial length in myopic children

Table 2 Performance of the machine learning algorithms and multiple linear regression model

	Algorithms	R²	R	RMSE	MAE	MSE
Traditional Statistical Method	Multiple Linear Regression	0.81	0.8985	0.4380	0.3455	0.1919
Machine Learning Methods	Linear Regression (linear)	0.86^*	0.9276^*	0.3782	0.2933	0.1430
	Linear Regression (Robust)	0.86^*	0.9276^*	0.3780^*	0.2929	0.1427^*
	SVM (linear)	0.86^*	0.9276^*	0.3781	0.2928^*	0.1429
	SVM (Quadratic)	0.85	0.9219	0.3916	0.3013	0.1533
	SVM (Cubic)	0.82	0.9055	0.4291	0.3263	0.1841
	Bagged Trees	0.77	0.8775	0.4820	0.3583	0.2323

SVM = support vector machine; RMSE = root mean square error; MAE = mean absolute error; MSE = mean squared error
Best values of indices are marked by an asterisk (*)

ISSN: 2326-0254