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fig4.pptx

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This document contains four figures comparing the performance of different machine learning algorithms (SVM, KNN, LightGBM, RF, GB) on training and testing data across four evaluation metrics: R^2 value, RMSE, MAE, and MAPE. LightGBM and RF performed the best overall with high R^2 values and lowest errors on both training and testing data according to the RMSE, MAE, and MAPE figures.

0.2
0.4
0.6
0.8
1.0
1.2
SVM KNN LightGBM RF GB
R
2
value
Training Testing
fig4a

fig4b
0.0
0.4
0.8
1.2
1.6
SVM KNN LightGBM RF GB
RMSE
value
(×10
-11
m/s)
Training
Testing

fig4c
0.0
0.2
0.4
0.6
0.8
1.0
SVM KNN LightGBM RF GB
MAE
value
(×10
-11
m/s)
Training
Testing

fig4d
0.0
0.2
0.4
0.6
0.8
1.0
1.2
SVM KNN LightGBM RF GB
MAPE
value
(%)
Training
Testing

More Related Content

fig4.pptx

1. 0.2 0.4 0.6 0.8 1.0 1.2 SVM KNN LightGBM RF GB R 2 value Training Testing fig4a

2. fig4b 0.0 0.4 0.8 1.2 1.6 SVM KNN LightGBM RF GB RMSE value (×10 -11 m/s) Training Testing

3. fig4c 0.0 0.2 0.4 0.6 0.8 1.0 SVM KNN LightGBM RF GB MAE value (×10 -11 m/s) Training Testing

4. fig4d 0.0 0.2 0.4 0.6 0.8 1.0 1.2 SVM KNN LightGBM RF GB MAPE value (%) Training Testing