Class WekaEvaluationValuePicker

  • All Implemented Interfaces:
    AdditionalInformationHandler, CleanUpHandler, Destroyable, GlobalInfoSupporter, LoggingLevelHandler, LoggingSupporter, OptionHandler, QuickInfoSupporter, ShallowCopySupporter<Actor>, SizeOfHandler, Stoppable, StoppableWithFeedback, VariablesInspectionHandler, VariableChangeListener, Actor, ErrorHandler, InputConsumer, OutputProducer, Serializable, Comparable

    public class WekaEvaluationValuePicker
    extends AbstractTransformer
    Picks a specific value from an evaluation object.

    Input/output:
    - accepts:
       weka.classifiers.Evaluation
       adams.flow.container.WekaEvaluationContainer
    - generates:
       java.lang.Double


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

    -logging-level <OFF|SEVERE|WARNING|INFO|CONFIG|FINE|FINER|FINEST> (property: loggingLevel)
        The logging level for outputting errors and debugging output.
        default: WARNING
        min-user-mode: Expert
     
    -name <java.lang.String> (property: name)
        The name of the actor.
        default: WekaEvaluationValuePicker
     
    -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
        min-user-mode: Expert
     
    -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
        min-user-mode: Expert
     
    -statistic <NUMBER_CORRECT|NUMBER_INCORRECT|NUMBER_UNCLASSIFIED|NUMBER_TOTAL|PERCENT_CORRECT|PERCENT_INCORRECT|PERCENT_UNCLASSIFIED|KAPPA_STATISTIC|MEAN_ABSOLUTE_ERROR|ROOT_MEAN_SQUARED_ERROR|RELATIVE_ABSOLUTE_ERROR|ROOT_RELATIVE_SQUARED_ERROR|CORRELATION_COEFFICIENT|SF_PRIOR_ENTROPY|SF_SCHEME_ENTROPY|SF_ENTROPY_GAIN|SF_MEAN_PRIOR_ENTROPY|SF_MEAN_SCHEME_ENTROPY|SF_MEAN_ENTROPY_GAIN|KB_INFORMATION|KB_MEAN_INFORMATION|KB_RELATIVE_INFORMATION|TRUE_POSITIVE_RATE|NUM_TRUE_POSITIVES|FALSE_POSITIVE_RATE|NUM_FALSE_POSITIVES|TRUE_NEGATIVE_RATE|NUM_TRUE_NEGATIVES|FALSE_NEGATIVE_RATE|NUM_FALSE_NEGATIVES|IR_PRECISION|IR_RECALL|F_MEASURE|MATTHEWS_CORRELATION_COEFFICIENT|AREA_UNDER_ROC|AREA_UNDER_PRC|WEIGHTED_TRUE_POSITIVE_RATE|WEIGHTED_FALSE_POSITIVE_RATE|WEIGHTED_TRUE_NEGATIVE_RATE|WEIGHTED_FALSE_NEGATIVE_RATE|WEIGHTED_IR_PRECISION|WEIGHTED_IR_RECALL|WEIGHTED_F_MEASURE|WEIGHTED_MATTHEWS_CORRELATION_COEFFICIENT|WEIGHTED_AREA_UNDER_ROC|WEIGHTED_AREA_UNDER_PRC|UNWEIGHTED_MACRO_F_MEASURE|UNWEIGHTED_MICRO_F_MEASURE|BIAS|MSLE|RSQUARED|SDR|RPD> (property: statisticValue)
        The evaluation value to extract.
        default: PERCENT_CORRECT
     
    -index <adams.data.weka.WekaLabelIndex> (property: classIndex)
        The class label index (eg used for AUC).
        default: first
        example: An index is a number starting with 1; apart from label names (case-sensitive), the following placeholders can be used as well: first, second, third, last_2, last_1, last; numeric indices can be enforced by preceding them with '#' (eg '#12'); label names can be surrounded by double quotes.
     
    Author:
    fracpete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form
    • Field Detail

      • m_ClassIndex

        protected WekaLabelIndex m_ClassIndex
        the index of the class label.
    • Constructor Detail

      • WekaEvaluationValuePicker

        public WekaEvaluationValuePicker()
    • Method Detail

      • setStatisticValue

        public void setStatisticValue​(EvaluationStatistic value)
        Sets the value to extract.
        Parameters:
        value - the value
      • getStatisticValue

        public EvaluationStatistic getStatisticValue()
        Returns the value to extract.
        Returns:
        the value
      • statisticValueTipText

        public String statisticValueTipText()
        Returns the tip text for this property.
        Returns:
        tip text for this property suitable for displaying in the GUI or for listing the options.
      • setClassIndex

        public void setClassIndex​(WekaLabelIndex value)
        Sets the class label index (1-based).
        Parameters:
        value - the label index
      • getClassIndex

        public WekaLabelIndex getClassIndex()
        Returns the current class label index (1-based).
        Returns:
        the label index
      • classIndexTipText

        public String classIndexTipText()
        Returns the tip text for this property.
        Returns:
        tip text for this property suitable for displaying in the GUI or for listing the options.
      • accepts

        public Class[] accepts()
        Returns the class that the consumer accepts.
        Returns:
        weka.classifiers.Evaluation.class, adams.flow.container.WekaEvaluationContainer.class
      • doExecute

        protected String doExecute()
        Executes the flow item.
        Specified by:
        doExecute in class AbstractActor
        Returns:
        null if everything is fine, otherwise error message
      • generates

        public Class[] generates()
        Returns the class of objects that it generates.
        Returns:
        java.lang.Double.class