adams.flow.transformer.MekaCrossValidationEvaluator
Cross-validates a Meka classifier on an incoming dataset. The classifier setup being used in the evaluation is a callable source outputting a Meka classifier.
Flow input/output:
- input: weka.core.Instances
- output: adams.flow.container.MekaResultContainer
Container information:
- adams.flow.container.MekaResultContainer:
- Result: result container; meka.core.Result
- Model: model object; java.lang.Object
The logging level for outputting errors and debugging output.
| command-line | -logging-level <OFF|SEVERE|WARNING|INFO|CONFIG|FINE|FINER|FINEST> |
| default | WARNING |
| min-user-mode | Expert |
The name of the actor.
| command-line | -name <java.lang.String> |
| default | MekaCrossValidationEvaluator |
The annotations to attach to this actor.
| command-line | -annotation <adams.core.base.BaseAnnotation> |
| default | |
If set to true, transformation is skipped and the input token is just forwarded as it is.
| command-line | -skip <boolean> |
| default | false |
If set to true, the flow execution at this level gets stopped in case this actor encounters an error; the error gets propagated; useful for critical actors.
| command-line | -stop-flow-on-error <boolean> |
| default | false |
| min-user-mode | Expert |
If enabled, then no errors are output in the console; Note: the enclosing actor handler must have this enabled as well.
| command-line | -silent <boolean> |
| default | false |
| min-user-mode | Expert |
The callable source actor for obtaining the classifier setup to cross-validate on the input data.
| command-line | -classifier <adams.flow.core.CallableActorReference> |
| default | MekaClassifierSetup |
The seed value for the cross-validation (used for randomization).
| command-line | -seed <long> |
| default | 1 |
The number of folds to use in the cross-validation; use -1 for leave-one-out cross-validation (LOOCV).
| command-line | -folds <int> |
| default | 10 |
| minimum | -1 |