adams.flow.transformer.WekaCrossValidationClustererEvaluator
Cross-validates a clusterer on an incoming dataset. The clusterer setup being used in the evaluation is a callable 'Clusterer' actor.
Flow input/output:
- input: weka.core.Instances
- output: adams.flow.container.WekaClusterEvaluationContainer
Container information:
- adams.flow.container.WekaClusterEvaluationContainer:
- Evaluation: cluster evaluation object; weka.clusterers.ClusterEvaluation
- Model: cluster model; java.lang.Object
- Log-likelohood: log likelihood of cross-validation; java.lang.Double
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 | WekaCrossValidationClustererEvaluator |
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 clusterer actor to cross-validate on the input data.
command-line | -clusterer <adams.flow.core.CallableActorReference> |
default | WekaClustererSetup |
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 |