Table 10:
Validation accuracies for the random-forest models.
| L | S | Fold 1 | Fold 2 | Fold 3 | Fold 4 | Average |
|---|---|---|---|---|---|---|
| 1 | 2 | 56.23 | 54.77 | 57.97 | 57.21 | 56.55 |
| 1 | 3000 | 56.31 | 54.73 | 58.05 | 57.06 | 56.54 |
| 1 | 1500 | 56.27 | 54.80 | 58.08 | 56.99 | 56.53 |
| 1 | 120 | 56.22 | 54.58 | 58.07 | 57.06 | 56.48 |
| 1 | 700 | 56.29 | 54.72 | 57.92 | 56.95 | 56.47 |
| 1 | 300 | 56.36 | 54.58 | 57.86 | 56.92 | 56.43 |
| 1 | 50 | 56.19 | 54.56 | 57.92 | 56.82 | 56.37 |
| 5 | 120 | 56.27 | 54.57 | 57.80 | 56.82 | 56.37 |
| 5 | 300 | 56.23 | 54.62 | 57.73 | 56.80 | 56.34 |
| 1 | 20 | 56.06 | 54.48 | 57.93 | 56.88 | 56.34 |
We report the top 10 performing models. L denotes the minimum number of samples required to be at a leaf and S denotes the minimum number of examples required to split each internal node. We experimented with the following values: L = {1,5,20,50,150,400,800,1500}, S = {2,20,50,120,300,700,1500,3000}.