WQD.5 - Random Forest
Completely unsupervised random forest method on Training data with ntree = 150 leads to the following error plot:

Importance of predictors are given in the following dotplot:

Accuracy improves from 50% to 67.7%.
| Quality Classification | |||
| Test Data | Low | Medium | High |
| Low | 378 | 277 | 17 |
| Medium | 219 | 726 | 201 |
| High | 7 | 83 | 276 |
| Accuracy | (378 + 726 + 276) / 2037 = 67.7% | ||