Modelling on Car-Sharing Serial Prediction Based on Machine Learning and Deep Learning

Table 8

Machine learning for historical data with weekends data evaluation results.

	MAE	MSE	RMSE	MAPE	RMSLE
XGBoost	0.07189	0.00969	0.09876	0.30527	0.07172
VAR	1.05771	1.19652	1.482066	0.98598	1.14989
SVM	1.14782	1.83432	1.68569	1.79397	1.2942
KNN	1.19799	2.77371	1.75573	1.91257	1.44645
(a) Class A
	MAE	MSE	RMSE	MAPE	RMSLE
XGBoost	0.09057	0.02244	0.15007	0.18352	0.05771
VAR	0.44645	0.36339	0.60281	0.13388	0.09025
SVM	0.72168	1.03896	1.01929	1.14777	0.78527
KNN	0.76351	1.40766	1.18639	1.24379	0.7216
(b) Class B
	MAE	MSE	RMSE	MAPE	RMSLE
XGBoost	0.1175	0.03476	0.18457	0.28931	0.1175
VAR	0.43805	0.34159	0.58445	0.50319	0.43805
SVM	0.81479	0.99398	0.99698	1.1251	0.57837
KNN	0.83915	1.86244	1.36463	1.22597	0.93895
(c) Class C
	MAE	MSE	RMSE	MAPE	RMSLE
XGBoost	0.03299	0.00314	0.05544	0.03984	0.02959
VAR	0.43452	0.34574	0.588	0.18361	0.43452
SVM	0.54589	0.69409	0.83352	1.16626	0.54589
KNN	0.61696	1.14954	1.07216	1.18884	0.89971
(d) Class D
	MAE	MSE	RMSE	MAPE	RMSLE
XGBoost	0.01878	0.00222	0.04717	0.00583	0.01878
VAR	0.08543	0.08481	0.29123	0.14278	0.08527
SVM	0.14422	0.11862	0.34426	0.53462	0.08543
KNN	0.27324	0.13282	0.36444	1.94985	0.37284
(e) Class E