Name

adams.flow.transformer.MekaClassifying


Synopsis

Uses a serialized model to perform predictions on the data being passed through.
The following order is used to obtain the model (when using AUTO):
1. model file present?
2. source actor present?
3. storage item present?


Additional information

Flow input/output:
- input: weka.core.Instance, adams.data.instance.WekaInstanceContainer
- output: adams.flow.container.WekaPredictionContainer, weka.core.Instance

Container information:
- adams.flow.container.WekaPredictionContainer:
   - Instance: data row used for prediction; weka.core.Instance
   - Classification: predicted value; java.lang.Double
   - Classification label: predicted label; java.lang.String
   - Distribution: class distribution; array of double
   - Range check: range check; java.lang.String
   - Abstention classification: predicted value that made classifier abstain; java.lang.Double
   - Abstention classification label: predicted label that made classifier abstain; java.lang.String
   - Abstention distribution: class distribution that made classifier abstain; array of double
   - Report: report for storing meta-data; adams.data.report.Report


Options