Research Article
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 |
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