Avionics Graphics Hardware Performance Prediction with Machine Learning

Table 4

Central tendencies of the prediction error distributions for each machine learning algorithm and for each validation dataset.

Validation dataset name	Supervised learning algorithm	RMSE (FPS)	Relative prediction error (%)	Mean absolute prediction error (FPS)	Median absolute prediction error (FPS)
#1	Random forest	2.71	2.12	1.36	0.45
	MART	9.37	10.15	6.85	4.86
	Neural net	2.29	1.99	1.26	0.50
#2	Random forest	10.87	8.74	5.85	2.06
	MART	16.53	17.65	12.16	10.39
	Neural net	7.90	8.50	5.16	3.51
#3	Random forest	5.94	5.98	4.10	2.79
	MART	9.99	10.60	7.51	6.15
	Neural net	2.97	3.03	2.39	2.13
#4	Random forest	15.80	9.12	10.94	3.98
	MART	30.20	18.78	22.53	15.02
	Neural net	4.02	2.58	3.10	3.01

Figures 6–9 present the error distribution of each nonparametric performance model for the four validation scenes.