| Issue | #Downvotes for this reason | By |
|---|
| -do-not-check-capabilities | If set, classifier capabilities are not checked before classifier is built (use with caution). | |
| E | The number of threads to use for batch prediction, which should be >= size of thread pool. (default 1) | default: 1 |
| H | Shrinkage parameter. (default 1) | default: 1.0 |
| I | Number of iterations. (current value 10) | default: 10 |
| L | Threshold on the improvement of the likelihood. (default -Double.MAX_VALUE) | default: -1.7976931348623157E308 |
| O | The size of the thread pool, for example, the number of cores in the CPU. (default 1) | default: 1 |
| P | Percentage of weight mass to base training on. (default 100, reduce to around 90 speed up) | default: 100 |
| Q | Use resampling instead of reweighting for boosting. | |
| S | Random number seed. (default 1) | default: 1 |
| W | Full name of base classifier. (default: weka.classifiers.trees.DecisionStump) | default: weka.classifiers.trees.DecisionStump |
| Z | Z max threshold for responses. (default 3) | default: 3.0 |
| batch-size | The desired batch size for batch prediction (default 100). | |
| num-decimal-places | The number of decimal places for the output of numbers in the model (default 2). | |
| output-debug-info | If set, classifier is run in debug mode and may output additional info to the console | |
| resume | Set whether classifier can continue training after performing therequested number of iterations. Note that setting this to true will retain certain data structures which can increase the size of the model. | |
| use-estimated-priors | Use estimated priors rather than uniform ones. |