Table 7 Performance metrics evaluation of ML models.
Attributes | R2 | MAE | MSE | RMSE |
|---|---|---|---|---|
Multilinear regression model | ||||
Tensile strength | 0.953 | 0.823 | 1.306 | 1.142 |
Flexural strength | 0.775 | 0.284 | 1.117 | 1.056 |
Impact strength | 0.801 | 0.834 | 1.093 | 1.045 |
Hardness | 0.835 | 0.862 | 1.303 | 1.141 |
Decision tree regression model | ||||
Tensile strength | -7.006 | 4.500 | 23.140 | 4.810 |
Flexural strength | -2.677 | 1.800 | 4.450 | 2.109 |
Impact strength | -16.537 | 3.050 | 9.856 | 3.139 |
Hardness | -9.817 | 2.350 | 6.085 | 2.466 |
Random forest regression model | ||||
Tensile strength | 0.968 | 0.829 | 0.906 | 0.951 |
Flexural strength | 0.939 | 0.489 | 0.299 | 0.546 |
Impact strength | 0.941 | 0.510 | 0.325 | 0.570 |
Hardness | 0.962 | 0.504 | 0.294 | 0.542 |
