|
Model |
R2 |
Mean Absolute Error |
Mean Squared Error |
|
K-Nearest Neighbors |
0.723446 |
7.497764 |
357.392135 |
|
Random Forest |
0.665746 |
7.558891 |
431.958693 |
|
Neural Network |
0.733759 |
7.037670 |
344.065457 |
|
Model |
R2 |
Mean Absolute Error |
Mean Squared Error |
|
K Nearest Neighbors |
0.750207 |
13.518466 |
796.466703 |
|
Random Forest |
0.790549 |
12.157173 |
667.836037 |
|
Neural Network |
0.819361 |
11.764073 |
575.968509 |
Table 1: Comparison of all three models in Round Hill dataset
Table 2: Comparison of all three models in Prairie Grass dataset
[ N.B: Random Forest and Neural Network both use randomness in their algorithm, hence their predictions fluctuate. Here, their performances are presented as the average of 10 experiments ]