WQD.5 - Random Forest

Printer-friendly versionPrinter-friendly version

Completely unsupervised random forest method on Training data with ntree = 150 leads to the following error plot:

error plot

Importance of predictors are given in the following dotplot:

dotplots of results

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%