| Issue | #Downvotes for this reason | By |
|---|
| W | weka.RandomTree(14) | Full name of base classifier. (default: weka.classifiers.trees.RandomTree) |
| -do-not-check-capabilities | If set, classifier capabilities are not checked before classifier is built (use with caution). | |
| B | Break ties randomly when several attributes look equally good. | |
| I | Number of iterations. (current value 10) | default: 10 |
| K | Number of attributes to randomly investigate. (default 0) (<1 = int(log_2(#predictors)+1)). | |
| M | Set minimum number of instances per leaf. (default 1) | |
| N | Number of folds for backfitting (default 0, no backfitting). | |
| S | Random number seed. (default 1) | default: 1 |
| U | Allow unclassified instances. | |
| V | Set minimum numeric class variance proportion of train variance for split (default 1e-3). | |
| W | Full name of base classifier. (default: weka.classifiers.trees.RandomTree) | default: weka.classifiers.trees.RandomTree |
| batch-size | The desired batch size for batch prediction (default 100). | |
| depth | The maximum depth of the tree, 0 for unlimited. (default 0) | |
| num-decimal-places | The number of decimal places for the output of numbers in the model (default 2). | |
| num-slots | Number of execution slots. (default 1 - i.e. no parallelism) (use 0 to auto-detect number of cores) | default: 1 |
| output-debug-info | If set, classifier is run in debug mode and may output additional info to the console |