Machine Learning Algorithms for Predicting Energy Consumption in Educational Buildings

Table 5

Predictions for performance evaluation using trained models.

Building	Method	R2	MSE	RMS	MAE	MAPE
CLAS	RF	0.8506	27.245	16.530	219.73	76.947
CLAS	LSTM	0.8669	11.0921	13.3036	79.0677	56.0298
CLAS	GBR	0.984	8.148	9.335	71.722	40.2587
NHAI	RF	0.479	56.293	20.439	47.78	8.45123
NHAI	LSTM	0.8372	27.10199	19.2844	33.0788	48.11382
NHAI	GBR	0.795	15.089	17.4370	32.675	52.57254
Cronkite	RF	0.89318	19.821	10.8491	117.704	56.54793
Cronkite	LSTM	0.76096	26.12360	7.3153	29.09945	64.8606
Cronkite	GBR	0.99817	9.1734	4.04234	16.3405	36.34167