Package weka.classifiers.evaluation

Class TwoClassStats

java.lang.Object
weka.classifiers.evaluation.TwoClassStats
All Implemented Interfaces:
RevisionHandler
public class TwoClassStats extends Object implements RevisionHandler
Encapsulates performance functions for two-class problems.
Version:
$Revision: 14381 $
Author:
Len Trigg (len@reeltwo.com)

  • Constructor Summary

    Constructors
    Constructor
    Description
    TwoClassStats(double tp, double fp, double tn, double fn)
    Creates the TwoClassStats with the given initial performance values.

  • Method Summary

    Modifier and Type
    Method
    Description
    ConfusionMatrix
    getConfusionMatrix()
    Generates a ConfusionMatrix representing the current two-class statistics, using class names "negative" and "positive".
    double
    getFallout()
    Calculate the fallout.
    double
    getFalseNegative()
    Gets the number of positive instances predicted as negative
    double
    getFalsePositive()
    Gets the number of negative instances predicted as positive
    double
    getFalsePositiveRate()
    Calculate the false positive rate.
    double
    getFMeasure()
    Calculate the F-Measure.
    double
    getPrecision()
    Calculate the precision.
    double
    getRecall()
    Calculate the recall.
    String
    getRevision()
    Returns the revision string.
    double
    getTrueNegative()
    Gets the number of negative instances predicted as negative
    double
    getTruePositive()
    Gets the number of positive instances predicted as positive
    double
    getTruePositiveRate()
    Calculate the true positive rate.
    void
    setFalseNegative(double fn)
    Sets the number of positive instances predicted as negative
    void
    setFalsePositive(double fp)
    Sets the number of negative instances predicted as positive
    void
    setTrueNegative(double tn)
    Sets the number of negative instances predicted as negative
    void
    setTruePositive(double tp)
    Sets the number of positive instances predicted as positive
    String
    toString()
    Returns a string containing the various performance measures for the current object

    Methods inherited from class java.lang.Object

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

  • Constructor Details

    • TwoClassStats

      public TwoClassStats(double tp, double fp, double tn, double fn)
      Creates the TwoClassStats with the given initial performance values.
      Parameters:
      tp - the number of correctly classified positives
      fp - the number of incorrectly classified negatives
      tn - the number of correctly classified negatives
      fn - the number of incorrectly classified positives

  • Method Details

    • setTruePositive

      public void setTruePositive(double tp)
      Sets the number of positive instances predicted as positive

    • setFalsePositive

      public void setFalsePositive(double fp)
      Sets the number of negative instances predicted as positive

    • setTrueNegative

      public void setTrueNegative(double tn)
      Sets the number of negative instances predicted as negative

    • setFalseNegative

      public void setFalseNegative(double fn)
      Sets the number of positive instances predicted as negative

    • getTruePositive

      public double getTruePositive()
      Gets the number of positive instances predicted as positive

    • getFalsePositive

      public double getFalsePositive()
      Gets the number of negative instances predicted as positive

    • getTrueNegative

      public double getTrueNegative()
      Gets the number of negative instances predicted as negative

    • getFalseNegative

      public double getFalseNegative()
      Gets the number of positive instances predicted as negative

    • getTruePositiveRate

      public double getTruePositiveRate()
      Calculate the true positive rate. This is defined as 

       correctly classified positives
 ------------------------------
       total positives
      Returns:
      the true positive rate

    • getFalsePositiveRate

      public double getFalsePositiveRate()
      Calculate the false positive rate. This is defined as 

       incorrectly classified negatives
 --------------------------------
        total negatives
      Returns:
      the false positive rate

    • getPrecision

      public double getPrecision()
      Calculate the precision. This is defined as 

       correctly classified positives
 ------------------------------
  total predicted as positive
      Returns:
      the precision

    • getRecall

      public double getRecall()
      Calculate the recall. This is defined as 

       correctly classified positives
 ------------------------------
       total positives

      (Which is also the same as the truePositiveRate.)

      Returns:
      the recall

    • getFMeasure

      public double getFMeasure()
      Calculate the F-Measure. This is defined as 

       2 * recall * precision
 ----------------------
   recall + precision
      Returns:
      the F-Measure

    • getFallout

      public double getFallout()
      Calculate the fallout. This is defined as 

       incorrectly classified negatives
 --------------------------------
   total predicted as positive
      Returns:
      the fallout

    • getConfusionMatrix

      public ConfusionMatrix getConfusionMatrix()
      Generates a ConfusionMatrix representing the current two-class statistics, using class names "negative" and "positive".
      Returns:
      a ConfusionMatrix.

    • toString

      public String toString()
      Returns a string containing the various performance measures for the current object
      Overrides:
      toString in class Object

    • getRevision

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