Table 1.
The parameters of the used classifiers.
| Group | Classifier | Parameters |
|---|---|---|
| Tree [[51], [52], [53]] | Fine | Number of splits: 100, Criteria: Gini |
| Medium | Number of splits: 20, Criteria: Gini | |
| Discriminant [54] | Linear Discriminant | Covariance structure is full. |
| SVM [55] | Cubic | Kernel: Cubic (3rd degree polynomial), C: 1, Multiclass: 1 vs 1 |
| Quadratic | Kernel: Quadratic (2nd degree polynomial), C: 1, Multiclass: 1 vs 1 | |
| Gaussian | Kernel: Gaussian, C: 1, Multiclass: 1 vs 1 | |
| Linear | Kernel: Linear, C: 1, Multiclass: 1 vs 1 | |
| k-NN [50] | Fine | k:1, Distance: City Block, Weight: Equal |
| Medium | k:10, Distance: Euclidean, Weight: Equal | |
| Coarse | k:100, Distance: Euclidean, Weight: Equal | |
| Cosine | k:10, Distance: Cosine, Weight: Equal | |
| Cubic | k:10, Distance: Cubic, Weight: Equal | |
| Weighted | k:10, Weight: Squared inverse Distance: Euclidean, | |
| Ensemble [56] | Bagged Tree | Method: Bag, Splits: 434, Learners: 30 Learner type: Decision tree, |
| Subspace discriminant | Subspace domain: 308,Method: Subspace, Learners: 30, Learner type: Discriminant | |
| Subspace k-NN | Subspace domain: 308, Method: Subspace, Learners: 30, Learner type: k-NN, |