Package weka.classifiers.evaluation.output.prediction

Class AnalogicalModelingOutput

  • All Implemented Interfaces:
    java.io.Serializable, weka.core.OptionHandler
    public class AnalogicalModelingOutput
extends weka.classifiers.evaluation.output.prediction.AbstractOutput
    This class implements a classification output scheme specific to the Analogical Modeling classifier. In particular, it allows the user to print gang effects and analogical sets. Valid options are: 

     -p <range>
    The range of attributes to print in addition to the classification.
    (default: none)
 
     -distribution
    Whether to turn on the output of the class distribution.
    Only for nominal class attributes.
    (default: off)
 
     -decimals <num>
    The number of digits after the decimal point.
    (default: 3)
 
     -file <path>
    The file to store the output in, instead of outputting it on stdout.
    Gets ignored if the supplied path is a directory.
    (default: .)
 
     -suppress
    In case the data gets stored in a file, then this flag can be used
    to suppress the regular output.
    (default: not suppressed)
 
     -summary
    Output short summary statistics
 
     -as
    Output the analogical set
 
     -gang
    Output gang effects
 
     -F <format>
    Format to print reports in. The options are 'human' and 'csv'. 'human' output is a human-readable, text-based
    table of some kind. 'csv', or comma-separated values, is intended to be machine-readable (for loading in Excel,
    Pandas, etc.), and contains strictly more data, such as the configuration parameters. Default is 'human'. If
    summary printing is turned on, this is always printed in the human-readable format.

    This output module enables detailed reporting on the results of the Analogical Modeling classifier, such as the analogical set and gang effects.

    See Also:
    Serialized Form

    • Field Summary

      Fields 
      Modifier and Type Field Description
      static weka.core.Tag[] TAGS_FORMATTER
      Define possible formatting methods

      • Fields inherited from class weka.classifiers.evaluation.output.prediction.AbstractOutput

        m_Attributes, m_Buffer, m_FileBuffer, m_Header, m_NumDecimals, m_OutputDistribution, m_OutputFile, m_SuppressOutput

    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      java.lang.String analogicalSetTipText()
      Returns the tip text for this property.
      protected void doPrintClassification​(double[] classDistribution, weka.core.Instance classifiedInstance, int index)  
      protected void doPrintClassification​(weka.classifiers.Classifier classifier, weka.core.Instance inst, int index)
      Make sure to call setHeader first, or this will throw a NullPointerException.
      protected void doPrintFooter()  
      protected void doPrintHeader()  
      java.lang.String gangsTipText()
      Returns the tip text for this property.
      boolean getAnalogicalSet()  
      java.lang.String getDisplay()  
      weka.core.SelectedTag getFormat()  
      boolean getGangs()  
      java.lang.String[] getOptions()
      Gets the current option settings for the OptionHandler.
      boolean getSummary()  
      java.lang.String globalInfo()  
      java.util.Enumeration<weka.core.Option> listOptions()
      Returns an enumeration of all the available options..
      void printClassification​(weka.classifiers.Classifier classifier, weka.core.Instance inst, int index)
      This is the function that is called in the GUI (ClassifierPanel); it has to be overridden here because the implementation in AbstractOutput calls doPrintClassification(double[], Instance, int) instead
      void setAnalogicalSet​(boolean value)  
      void setFormat​(weka.core.SelectedTag newMode)  
      void setGangs​(boolean value)  
      void setOptions​(java.lang.String[] options)
      Sets the OptionHandler's options using the given list.
      void setSummary​(boolean value)  
      java.lang.String summaryTipText()
      Returns the tip text for this property.

      • Methods inherited from class weka.classifiers.evaluation.output.prediction.AbstractOutput

        append, attributesTipText, checkBasic, checkHeader, fromCommandline, generatesOutput, getAttributes, getBuffer, getDefaultNumDecimals, getHeader, getNumDecimals, getOutputDistribution, getOutputFile, getSuppressOutput, numDecimalsTipText, outputDistributionTipText, outputFileTipText, preProcessInstance, print, print, printClassification, printClassifications, printClassifications, printFooter, printHeader, setAttributes, setBuffer, setHeader, setNumDecimals, setOutputDistribution, setOutputFile, setSuppressOutput, suppressOutputTipText

      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    • Field Detail

      • TAGS_FORMATTER

        public static final weka.core.Tag[] TAGS_FORMATTER
        Define possible formatting methods

    • Constructor Detail

      • AnalogicalModelingOutput

        public AnalogicalModelingOutput()

    • Method Detail

      • getFormat

        public weka.core.SelectedTag getFormat()
        Returns:
        Selected formatter

      • setFormat

        public void setFormat​(weka.core.SelectedTag newMode)
        Parameters:
        newMode - tag indicating which formatter to use
        Throws:
        java.lang.IllegalArgumentException - if input is not a known formatter.

      • globalInfo

        public java.lang.String globalInfo()
        Specified by:
        globalInfo in class weka.classifiers.evaluation.output.prediction.AbstractOutput

      • getDisplay

        public java.lang.String getDisplay()
        Specified by:
        getDisplay in class weka.classifiers.evaluation.output.prediction.AbstractOutput

      • doPrintHeader

        protected void doPrintHeader()
        Specified by:
        doPrintHeader in class weka.classifiers.evaluation.output.prediction.AbstractOutput

      • printClassification

        public void printClassification​(weka.classifiers.Classifier classifier,
                                weka.core.Instance inst,
                                int index)
                         throws java.lang.Exception
        This is the function that is called in the GUI (ClassifierPanel); it has to be overridden here because the implementation in AbstractOutput calls doPrintClassification(double[], Instance, int) instead
        Overrides:
        printClassification in class weka.classifiers.evaluation.output.prediction.AbstractOutput
        Throws:
        java.lang.Exception

      • doPrintClassification

        protected void doPrintClassification​(weka.classifiers.Classifier classifier,
                                     weka.core.Instance inst,
                                     int index)
                              throws java.lang.Exception
        Make sure to call setHeader first, or this will throw a NullPointerException.
        Specified by:
        doPrintClassification in class weka.classifiers.evaluation.output.prediction.AbstractOutput
        Throws:
        java.lang.Exception

      • doPrintClassification

        protected void doPrintClassification​(double[] classDistribution,
                                     weka.core.Instance classifiedInstance,
                                     int index)
        Specified by:
        doPrintClassification in class weka.classifiers.evaluation.output.prediction.AbstractOutput

      • doPrintFooter

        protected void doPrintFooter()
        Specified by:
        doPrintFooter in class weka.classifiers.evaluation.output.prediction.AbstractOutput

      • listOptions

        public java.util.Enumeration<weka.core.Option> listOptions()
        Returns an enumeration of all the available options..
        Specified by:
        listOptions in interface weka.core.OptionHandler
        Overrides:
        listOptions in class weka.classifiers.evaluation.output.prediction.AbstractOutput
        Returns:
        an enumeration of all available options.

      • setOptions

        public void setOptions​(java.lang.String[] options)
                throws java.lang.Exception
        Sets the OptionHandler's options using the given list. All options will be set (or reset) during this call (i.e. incremental setting of options is not possible).

        Valid options are: 

         -p <range>
    The range of attributes to print in addition to the classification.
    (default: none)
 
         -distribution
    Whether to turn on the output of the class distribution.
    Only for nominal class attributes.
    (default: off)
 
         -decimals <num>
    The number of digits after the decimal point.
    (default: 3)
 
         -file <path>
    The file to store the output in, instead of outputting it on stdout.
    Gets ignored if the supplied path is a directory.
    (default: .)
 
         -suppress
    In case the data gets stored in a file, then this flag can be used
    to suppress the regular output.
    (default: not suppressed)
 
         -summary
    Output short summary statistics
 
         -as
    Output the analogical set
 
         -gang
    Output gang effects
 
         -F <format>
    Format to print reports in. The options are 'human' and 'csv'. 'human' output is a human-readable, text-based
    table of some kind. 'csv', or comma-separated values, is intended to be machine-readable (for loading in Excel,
    Pandas, etc.), and contains strictly more data, such as the configuration parameters. Default is 'human'. If
    summary printing is turned on, this is always printed in the human-readable format.

        *

        Specified by:
        setOptions in interface weka.core.OptionHandler
        Overrides:
        setOptions in class weka.classifiers.evaluation.output.prediction.AbstractOutput
        Parameters:
        options - the list of options as an array of strings
        Throws:
        java.lang.Exception - if an option is not supported

      • getOptions

        public java.lang.String[] getOptions()
        Gets the current option settings for the OptionHandler.
        Specified by:
        getOptions in interface weka.core.OptionHandler
        Overrides:
        getOptions in class weka.classifiers.evaluation.output.prediction.AbstractOutput
        Returns:
        the list of current option settings as an array of strings

      • setGangs

        public void setGangs​(boolean value)
        Parameters:
        value - whether gang effects will be printed

      • getGangs

        public boolean getGangs()
        Returns:
        whether gang effects will be printed

      • gangsTipText

        public java.lang.String gangsTipText()
        Returns the tip text for this property.
        Returns:
        tip text for this property suitable for displaying in the GUI

      • setSummary

        public void setSummary​(boolean value)
        Parameters:
        value - whether a summary is to be printed

      • getSummary

        public boolean getSummary()
        Returns:
        whether a summary will be printed

      • summaryTipText

        public java.lang.String summaryTipText()
        Returns the tip text for this property.
        Returns:
        tip text for this property suitable for displaying in the GUI

      • getAnalogicalSet

        public boolean getAnalogicalSet()
        Returns:
        true if the analogical set will be printed

      • setAnalogicalSet

        public void setAnalogicalSet​(boolean value)
        Parameters:
        value - True if the analogical set should be printed

      • analogicalSetTipText

        public java.lang.String analogicalSetTipText()
        Returns the tip text for this property.
        Returns:
        tip text for this property suitable for displaying in the GUI