Package weka.classifiers.functions

Class FromPredictions

  • All Implemented Interfaces:
    adams.core.Destroyable, adams.core.GlobalInfoSupporter, adams.core.logging.LoggingLevelHandler, adams.core.logging.LoggingSupporter, adams.core.option.OptionHandler, adams.core.SizeOfHandler, Serializable, weka.classifiers.Classifier, weka.core.CapabilitiesHandler, weka.core.OptionHandler
    public class FromPredictions
extends AbstractSimpleClassifier
    Encapsulates predictions from a spreadsheet. Dummy classifier for the Investigator.
    Author:
    FracPete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form

    • Field Summary

      Fields 
      Modifier and Type Field Description
      protected adams.data.spreadsheet.SpreadSheetColumnIndex m_Actual
      the column with the actual values.
      protected int m_ActualIndex
      the actual column index.
      protected adams.data.spreadsheet.SpreadSheetColumnRange m_Additional
      the additional columns in the spreadsheet to add to the plot containers.
      protected int[] m_AdditionalIndices
      the additional column indices.
      protected adams.data.spreadsheet.SpreadSheetUnorderedColumnRange m_ClassDistribution
      the class distribution columns (if any).
      protected int[] m_ClassDistributionIndices
      the class distribution column indices.
      protected adams.data.spreadsheet.SpreadSheetColumnIndex m_Predicted
      the column with the predicted values.
      protected int m_PredictedIndex
      the predicted column index.
      protected adams.data.spreadsheet.SpreadSheet m_Predictions
      the actual predictions.
      protected adams.core.io.PlaceholderFile m_PredictionsFile
      the predictions to use.
      protected adams.data.io.input.SpreadSheetReader m_Reader
      the spreadsheet reader to use.
      protected adams.data.spreadsheet.SpreadSheetColumnIndex m_Weight
      the column with the error values (optional).
      protected int m_WeightIndex
      the weight column index.

      • Fields inherited from class adams.core.option.AbstractOptionHandler

        m_OptionManager

      • Fields inherited from class adams.core.logging.LoggingObject

        m_Logger, m_LoggingIsEnabled, m_LoggingLevel

    • Constructor Summary

      Constructors 
      Constructor Description
      FromPredictions()  

    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      String actualTipText()
      Returns the tip text for this property.
      String additionalTipText()
      Returns the tip text for this property.
      void buildClassifier​(weka.core.Instances data)
      Just loads the predictions.
      String classDistributionTipText()
      Returns the tip text for this property.
      double classifyInstance​(weka.core.Instance instance)
      Always returns 0.
      void defineOptions()
      Adds options to the internal list of options.
      adams.data.spreadsheet.SpreadSheetColumnIndex getActual()
      Returns the column with the actual values.
      int getActualIndex()
      Returns the actual 0-based index.
      adams.data.spreadsheet.SpreadSheetColumnRange getAdditional()
      Returns the additional columns to add to the plot containers.
      int[] getAdditionalIndices()
      Returns the 0-based indices of the additional columns.
      adams.data.spreadsheet.SpreadSheetUnorderedColumnRange getClassDistribution()
      Returns the class distribution columns.
      int[] getClassDistributionIndices()
      Returns the 0-based indices of the class distribution columns.
      adams.data.spreadsheet.SpreadSheetColumnIndex getPredicted()
      Returns the column with the predicted values.
      int getPredictedIndex()
      Returns the predicted 0-based index.
      adams.data.spreadsheet.SpreadSheet getPredictions()
      Returns the predictions that were loaded.
      adams.core.io.PlaceholderFile getPredictionsFile()
      Returns the file with the predictions.
      adams.data.io.input.SpreadSheetReader getReader()
      Returns the spreadsheet reader to use.
      adams.data.spreadsheet.SpreadSheetColumnIndex getWeight()
      Returns the column with the weight values.
      int getWeightIndex()
      Returns the weight 0-based index.
      String globalInfo()
      Returns a string describing the object.
      String predictedTipText()
      Returns the tip text for this property.
      String predictionsFileTipText()
      Returns the tip text for this property.
      String readerTipText()
      Returns the tip text for this property.
      void setActual​(adams.data.spreadsheet.SpreadSheetColumnIndex value)
      Sets the column with the actual values.
      void setAdditional​(adams.data.spreadsheet.SpreadSheetColumnRange value)
      Sets the additional columns to add to the plot containers.
      void setClassDistribution​(adams.data.spreadsheet.SpreadSheetUnorderedColumnRange value)
      Sets the class distribution columns.
      void setPredicted​(adams.data.spreadsheet.SpreadSheetColumnIndex value)
      Sets the column with the predicted values.
      void setPredictionsFile​(adams.core.io.PlaceholderFile value)
      Sets the file with the predictions.
      void setReader​(adams.data.io.input.SpreadSheetReader value)
      Sets the spreadsheet reader to use.
      void setWeight​(adams.data.spreadsheet.SpreadSheetColumnIndex value)
      Sets the column with the weight values.
      String weightTipText()
      Returns the tip text for this property.

      • Methods inherited from class adams.core.option.AbstractOptionHandler

        cleanUpOptions, destroy, finishInit, getDefaultLoggingLevel, getOptionManager, initialize, loggingLevelTipText, newOptionManager, reset, toCommandLine, toString

      • Methods inherited from class adams.core.logging.CustomLoggingLevelObject

        setLoggingLevel

      • Methods inherited from class adams.core.logging.LoggingObject

        configureLogger, getLogger, getLoggingLevel, initializeLogging, isLoggingEnabled, sizeOf

      • Methods inherited from interface adams.core.logging.LoggingLevelHandler

        getLoggingLevel

    • Field Detail

      • m_PredictionsFile

        protected adams.core.io.PlaceholderFile m_PredictionsFile
        the predictions to use.

      • m_Reader

        protected adams.data.io.input.SpreadSheetReader m_Reader
        the spreadsheet reader to use.

      • m_Actual

        protected adams.data.spreadsheet.SpreadSheetColumnIndex m_Actual
        the column with the actual values.

      • m_ActualIndex

        protected int m_ActualIndex
        the actual column index.

      • m_Predicted

        protected adams.data.spreadsheet.SpreadSheetColumnIndex m_Predicted
        the column with the predicted values.

      • m_PredictedIndex

        protected int m_PredictedIndex
        the predicted column index.

      • m_Weight

        protected adams.data.spreadsheet.SpreadSheetColumnIndex m_Weight
        the column with the error values (optional).

      • m_WeightIndex

        protected int m_WeightIndex
        the weight column index.

      • m_ClassDistribution

        protected adams.data.spreadsheet.SpreadSheetUnorderedColumnRange m_ClassDistribution
        the class distribution columns (if any).

      • m_ClassDistributionIndices

        protected int[] m_ClassDistributionIndices
        the class distribution column indices.

      • m_Additional

        protected adams.data.spreadsheet.SpreadSheetColumnRange m_Additional
        the additional columns in the spreadsheet to add to the plot containers.

      • m_AdditionalIndices

        protected int[] m_AdditionalIndices
        the additional column indices.

      • m_Predictions

        protected adams.data.spreadsheet.SpreadSheet m_Predictions
        the actual predictions.

    • Constructor Detail

      • FromPredictions

        public FromPredictions()

    • Method Detail

      • globalInfo

        public String globalInfo()
        Returns a string describing the object.
        Specified by:
        globalInfo in interface adams.core.GlobalInfoSupporter
        Specified by:
        globalInfo in class adams.core.option.AbstractOptionHandler
        Returns:
        a description suitable for displaying in the gui

      • defineOptions

        public void defineOptions()
        Adds options to the internal list of options.
        Specified by:
        defineOptions in interface adams.core.option.OptionHandler
        Overrides:
        defineOptions in class adams.core.option.AbstractOptionHandler

      • setPredictionsFile

        public void setPredictionsFile​(adams.core.io.PlaceholderFile value)
        Sets the file with the predictions.
        Parameters:
        value - the file

      • getPredictionsFile

        public adams.core.io.PlaceholderFile getPredictionsFile()
        Returns the file with the predictions.
        Returns:
        the file

      • predictionsFileTipText

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

      • setReader

        public void setReader​(adams.data.io.input.SpreadSheetReader value)
        Sets the spreadsheet reader to use.
        Parameters:
        value - the reader

      • getReader

        public adams.data.io.input.SpreadSheetReader getReader()
        Returns the spreadsheet reader to use.
        Returns:
        the reader

      • readerTipText

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

      • setActual

        public void setActual​(adams.data.spreadsheet.SpreadSheetColumnIndex value)
        Sets the column with the actual values.
        Parameters:
        value - the column

      • getActual

        public adams.data.spreadsheet.SpreadSheetColumnIndex getActual()
        Returns the column with the actual values.
        Returns:
        the range

      • actualTipText

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

      • setPredicted

        public void setPredicted​(adams.data.spreadsheet.SpreadSheetColumnIndex value)
        Sets the column with the predicted values.
        Parameters:
        value - the column

      • getPredicted

        public adams.data.spreadsheet.SpreadSheetColumnIndex getPredicted()
        Returns the column with the predicted values.
        Returns:
        the range

      • predictedTipText

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

      • setWeight

        public void setWeight​(adams.data.spreadsheet.SpreadSheetColumnIndex value)
        Sets the column with the weight values.
        Parameters:
        value - the column

      • getWeight

        public adams.data.spreadsheet.SpreadSheetColumnIndex getWeight()
        Returns the column with the weight values.
        Returns:
        the column

      • weightTipText

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

      • setClassDistribution

        public void setClassDistribution​(adams.data.spreadsheet.SpreadSheetUnorderedColumnRange value)
        Sets the class distribution columns.
        Parameters:
        value - the columns

      • getClassDistribution

        public adams.data.spreadsheet.SpreadSheetUnorderedColumnRange getClassDistribution()
        Returns the class distribution columns.
        Returns:
        the columns

      • classDistributionTipText

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

      • setAdditional

        public void setAdditional​(adams.data.spreadsheet.SpreadSheetColumnRange value)
        Sets the additional columns to add to the plot containers.
        Parameters:
        value - the columns

      • getAdditional

        public adams.data.spreadsheet.SpreadSheetColumnRange getAdditional()
        Returns the additional columns to add to the plot containers.
        Returns:
        the columns

      • additionalTipText

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

      • getPredictions

        public adams.data.spreadsheet.SpreadSheet getPredictions()
        Returns the predictions that were loaded.
        Returns:
        the predictions, null if not available

      • getActualIndex

        public int getActualIndex()
        Returns the actual 0-based index.
        Returns:
        the index, -1 if not initialized

      • getPredictedIndex

        public int getPredictedIndex()
        Returns the predicted 0-based index.
        Returns:
        the index, -1 if not initialized

      • getWeightIndex

        public int getWeightIndex()
        Returns the weight 0-based index.
        Returns:
        the index, -1 if not initialized

      • getClassDistributionIndices

        public int[] getClassDistributionIndices()
        Returns the 0-based indices of the class distribution columns.
        Returns:
        the indices, 0-length array if not initialized or not used

      • getAdditionalIndices

        public int[] getAdditionalIndices()
        Returns the 0-based indices of the additional columns.
        Returns:
        the indices, 0-length array if not initialized or not used

      • buildClassifier

        public void buildClassifier​(weka.core.Instances data)
                     throws Exception
        Just loads the predictions.
        Parameters:
        data - ignored
        Throws:
        Exception - if loading of predictions failed

      • classifyInstance

        public double classifyInstance​(weka.core.Instance instance)
                        throws Exception
        Always returns 0.
        Specified by:
        classifyInstance in interface weka.classifiers.Classifier
        Overrides:
        classifyInstance in class AbstractSimpleClassifier
        Parameters:
        instance - the instance to be classified
        Returns:
        always 0
        Throws:
        Exception - never thrown