Package adams.flow.transformer

Class WekaPredictionsToSpreadSheet

  • All Implemented Interfaces:
    AdditionalInformationHandler, ClassCrossReference, CleanUpHandler, CrossReference, Destroyable, GlobalInfoSupporter, LoggingLevelHandler, LoggingSupporter, OptionHandler, QuickInfoSupporter, ShallowCopySupporter<Actor>, SizeOfHandler, Stoppable, StoppableWithFeedback, VariablesInspectionHandler, VariableChangeListener, Actor, ErrorHandler, InputConsumer, OutputProducer, Serializable, Comparable
    public class WekaPredictionsToSpreadSheet
extends AbstractWekaPredictionsTransformer
implements ClassCrossReference
    Generates a SpreadSheet object from the predictions of an Evaluation object.

    See also:
    adams.flow.transformer.WekaSpreadSheetToPredictions

    Input/output:
    - accepts:
       weka.classifiers.Evaluation
       adams.flow.container.WekaEvaluationContainer
    - generates:
       adams.data.spreadsheet.SpreadSheet


    Container information:
    - adams.flow.container.WekaEvaluationContainer: Evaluation, Model, Prediction output, Original indices 

    -logging-level <OFF|SEVERE|WARNING|INFO|CONFIG|FINE|FINER|FINEST> (property: loggingLevel)
    The logging level for outputting errors and debugging output.
    default: WARNING
 
    -name <java.lang.String> (property: name)
    The name of the actor.
    default: WekaPredictionsToSpreadSheet
 
    -annotation <adams.core.base.BaseAnnotation> (property: annotations)
    The annotations to attach to this actor.
    default: 
 
    -skip <boolean> (property: skip)
    If set to true, transformation is skipped and the input token is just forwarded 
    as it is.
    default: false
 
    -stop-flow-on-error <boolean> (property: stopFlowOnError)
    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.
    default: false
 
    -silent <boolean> (property: silent)
    If enabled, then no errors are output in the console; Note: the enclosing 
    actor handler must have this enabled as well.
    default: false
 
    -add-index <boolean> (property: addLabelIndex)
    If set to true, then the label is prefixed with the index.
    default: false
 
    -error <boolean> (property: showError)
    If set to true, then the error will be displayed as well.
    default: false
 
    -absolute-error <boolean> (property: useAbsoluteError)
    If set to true, then the error will be absolute (no direction).
    default: true
 
    -probability <boolean> (property: showProbability)
    If set to true, then the probability of the prediction will be displayed 
    as well (only for nominal class attributes).
    default: false
 
    -distribution <boolean> (property: showDistribution)
    If set to true, then the class distribution will be displayed as well (only 
    for nominal class attributes).
    default: false
 
    -weight <boolean> (property: showWeight)
    If set to true, then the instance weight will be displayed as well.
    default: false
 
    -use-original-indices <boolean> (property: useOriginalIndices)
    If set to true, the input token is a adams.flow.container.WekaEvaluationContainer 
    and it contains the original indices ('Original indices') then the output 
    will get aligned with the original data.
    default: false
 
    -test-attributes <adams.core.Range> (property: testAttributes)
    The range of attributes from the test set to add to the output (if test
    data available).
    default:
    example: A range is a comma-separated list of single 1-based indices or sub-ranges of indices ('start-end'); 'inv(...)' inverts the range '...'; the following placeholders can be used as well: first, second, third, last_2, last_1, last
 
    -measures-prefix <java.lang.String> (property: measuresPrefix)
    The prefix to use for the measure attributes being output.
    default:
    Author:
    fracpete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form

    • Constructor Detail

      • WekaPredictionsToSpreadSheet

        public WekaPredictionsToSpreadSheet()