weka.classifiers.evaluation

## Class NominalPrediction

- java.lang.Object
- - weka.classifiers.evaluation.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: 8034 $
  Author:
    Len Trigg (len@reeltwo.com)
  See Also:
    Serialized Form

- - ### Field Summary

    - ### Fields inherited from interface weka.classifiers.evaluation.Prediction

      `MISSING_VALUE`

  - ### Constructor Summary

    Constructors
    Constructor and 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

    Methods
    Modifier and Type | Method and 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