The most efficient variables for each machine learning method when using five MINT-selected features. The Mean Validation Score is the accuracy which the best parameters achieved. Rows are as in Table 3.
| Hyperparameter Optimization Results (using 5 MINT features) . | ||||
|---|---|---|---|---|
| . | RF . | ADA . | EXT . | GBT . |
| n_estimators | 64 | 512 | 64 | 256 |
| max_features | 1 | 1 | 3 | 1 |
| min_samples_leaf | 1 | 3 | 3 | 10 |
| criterion | entropy | entropy | gini | - |
| min_samples_split | 10 | 3 | 3 | 10 |
| max_depth | 3 | 4 | None | 9 |
| learning_rate | - | 0.01 | - | 0.01 |
| Mean Validation Score | 0.974 | 0.974 | 0.973 | 0.974 |
| Standard Deviation | 0.006 | 0.006 | 0.005 | 0.006 |
| Hyperparameter Optimization Results (using 5 MINT features) . | ||||
|---|---|---|---|---|
| . | RF . | ADA . | EXT . | GBT . |
| n_estimators | 64 | 512 | 64 | 256 |
| max_features | 1 | 1 | 3 | 1 |
| min_samples_leaf | 1 | 3 | 3 | 10 |
| criterion | entropy | entropy | gini | - |
| min_samples_split | 10 | 3 | 3 | 10 |
| max_depth | 3 | 4 | None | 9 |
| learning_rate | - | 0.01 | - | 0.01 |
| Mean Validation Score | 0.974 | 0.974 | 0.973 | 0.974 |
| Standard Deviation | 0.006 | 0.006 | 0.005 | 0.006 |
The most efficient variables for each machine learning method when using five MINT-selected features. The Mean Validation Score is the accuracy which the best parameters achieved. Rows are as in Table 3.
| Hyperparameter Optimization Results (using 5 MINT features) . | ||||
|---|---|---|---|---|
| . | RF . | ADA . | EXT . | GBT . |
| n_estimators | 64 | 512 | 64 | 256 |
| max_features | 1 | 1 | 3 | 1 |
| min_samples_leaf | 1 | 3 | 3 | 10 |
| criterion | entropy | entropy | gini | - |
| min_samples_split | 10 | 3 | 3 | 10 |
| max_depth | 3 | 4 | None | 9 |
| learning_rate | - | 0.01 | - | 0.01 |
| Mean Validation Score | 0.974 | 0.974 | 0.973 | 0.974 |
| Standard Deviation | 0.006 | 0.006 | 0.005 | 0.006 |
| Hyperparameter Optimization Results (using 5 MINT features) . | ||||
|---|---|---|---|---|
| . | RF . | ADA . | EXT . | GBT . |
| n_estimators | 64 | 512 | 64 | 256 |
| max_features | 1 | 1 | 3 | 1 |
| min_samples_leaf | 1 | 3 | 3 | 10 |
| criterion | entropy | entropy | gini | - |
| min_samples_split | 10 | 3 | 3 | 10 |
| max_depth | 3 | 4 | None | 9 |
| learning_rate | - | 0.01 | - | 0.01 |
| Mean Validation Score | 0.974 | 0.974 | 0.973 | 0.974 |
| Standard Deviation | 0.006 | 0.006 | 0.005 | 0.006 |
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