Table 1.

Comparison of performance metrics of different regressor models for 10 × 10 metasurface array.

Performance Metrics	Regressors
	Support Vector Regressor	Decision Tree	Random Forest	Gradient Boosting	Gaussian Process
Mean Absolute Error	0.6322	1.3728	0.8159	0.7813	0.5871
Mean Squared Error	0.9216	3.8664	1.3917	1.3830	0.8190
R${}^2$ Score *	0.9111	0.5321	0.8261	0.8269	0.9216

* In regression, the R${}^2$ score, which is the coefficient of determination, is a statistical measure of how well the regression predictions approximate the real data points.