Package weka.classifiers.evaluation

Class NominalPrediction

  • All Implemented Interfaces:
    java.io.Serializable, Prediction, RevisionHandler
    public class NominalPrediction
extends java.lang.Object
implements Prediction, java.io.Serializable, RevisionHandler
    Encapsulates an evaluatable nominal prediction: the predicted probability distribution plus the actual class value.
    Version:
    $Revision: 1.12 $
    Author:
    Len Trigg (len@reeltwo.com)
    See Also:
    Serialized Form

    • Constructor Summary

      Constructors 
      Constructor Description
      NominalPrediction​(double actual, double[] distribution)
      Creates the NominalPrediction object with a default weight of 1.0.
      NominalPrediction​(double actual, double[] distribution, double weight)
      Creates the NominalPrediction object.

    • Method Summary

      All Methods Static Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      double actual()
      Gets the actual class value.
      double[] distribution()
      Gets the predicted probabilities
      java.lang.String getRevision()
      Returns the revision string.
      static double[] makeDistribution​(double predictedClass, int numClasses)
      Convert a single prediction into a probability distribution with all zero probabilities except the predicted value which has probability 1.0.
      static double[] makeUniformDistribution​(int numClasses)
      Creates a uniform probability distribution -- where each of the possible classes is assigned equal probability.
      double margin()
      Calculates the prediction margin.
      double predicted()
      Gets the predicted class value.
      java.lang.String toString()
      Gets a human readable representation of this prediction.
      double weight()
      Gets the weight assigned to this prediction.

      • Methods inherited from class java.lang.Object

        equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

    • Constructor Detail

      • NominalPrediction

        public NominalPrediction​(double actual,
                         double[] distribution)
        Creates the NominalPrediction object with a default weight of 1.0.
        Parameters:
        actual - the actual value, or MISSING_VALUE.
        distribution - the predicted probability distribution. Use NominalPrediction.makeDistribution() if you only know the predicted value.

      • NominalPrediction

        public NominalPrediction​(double actual,
                         double[] distribution,
                         double weight)
        Creates the NominalPrediction object.
        Parameters:
        actual - the actual value, or MISSING_VALUE.
        distribution - the predicted probability distribution. Use NominalPrediction.makeDistribution() if you only know the predicted value.
        weight - the weight assigned to the prediction.

    • Method Detail

      • distribution

        public double[] distribution()
        Gets the predicted probabilities
        Returns:
        the predicted probabilities

      • actual

        public double actual()
        Gets the actual class value.
        Specified by:
        actual in interface Prediction
        Returns:
        the actual class value, or MISSING_VALUE if no prediction was made.

      • predicted

        public double predicted()
        Gets the predicted class value.
        Specified by:
        predicted in interface Prediction
        Returns:
        the predicted class value, or MISSING_VALUE if no prediction was made.

      • weight

        public double weight()
        Gets the weight assigned to this prediction. This is typically the weight of the test instance the prediction was made for.
        Specified by:
        weight in interface Prediction
        Returns:
        the weight assigned to this prediction.

      • margin

        public double margin()
        Calculates the prediction margin. This is defined as the difference between the probability predicted for the actual class and the highest predicted probability of the other classes.
        Returns:
        the margin for this prediction, or MISSING_VALUE if either the actual or predicted value is missing.

      • makeDistribution

        public static double[] makeDistribution​(double predictedClass,
                                        int numClasses)
        Convert a single prediction into a probability distribution with all zero probabilities except the predicted value which has probability 1.0. If no prediction was made, all probabilities are zero.
        Parameters:
        predictedClass - the index of the predicted class, or MISSING_VALUE if no prediction was made.
        numClasses - the number of possible classes for this nominal prediction.
        Returns:
        the probability distribution.

      • makeUniformDistribution

        public static double[] makeUniformDistribution​(int numClasses)
        Creates a uniform probability distribution -- where each of the possible classes is assigned equal probability.
        Parameters:
        numClasses - the number of possible classes for this nominal prediction.
        Returns:
        the probability distribution.

      • toString

        public java.lang.String toString()
        Gets a human readable representation of this prediction.
        Overrides:
        toString in class java.lang.Object
        Returns:
        a human readable representation of this prediction.

      • getRevision

        public java.lang.String getRevision()
        Returns the revision string.
        Specified by:
        getRevision in interface RevisionHandler
        Returns:
        the revision