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Class weka.classifiers.evaluation.ConfusionMatrix

java.lang.Object
    |
    +----weka.core.Matrix
            |
            +----weka.classifiers.evaluation.ConfusionMatrix

public class ConfusionMatrix
extends Matrix
Cells of this matrix correspond to counts of the number (or weight) of predictions for each actual value / predicted value combination.

Version:
$Revision: 1.4 $
Author:
Len Trigg (len@intelligenesis.net)

Constructor Index

 o ConfusionMatrix(String[])
Creates the confusion matrix with the given class names.

Method Index

 o addPrediction(NominalPrediction)
Includes a prediction in the confusion matrix.
 o addPredictions(FastVector)
Includes a whole bunch of predictions in the confusion matrix.
 o className(int)
Gets the name of one of the classes.
 o clone()
Creates and returns a clone of this object.
 o correct()
Gets the number of correct classifications (that is, for which a correct prediction was made).
 o errorRate()
Returns the estimated error rate.
 o getTwoClassStats(int)
Gets the performance with respect to one of the classes as a TwoClassStats object.
 o incorrect()
Gets the number of incorrect classifications (that is, for which an incorrect prediction was made).
 o makeWeighted(CostMatrix)
Makes a copy of this ConfusionMatrix after applying the supplied CostMatrix to the cells.
 o size()
Gets the number of classes.
 o toString()
Calls toString() with a default title.
 o toString(String)
Outputs the performance statistics as a classification confusion matrix.
 o total()
Gets the number of predictions that were made (actually the sum of the weights of predictions where the class value was known).

Constructor Detail

 o ConfusionMatrix
public ConfusionMatrix(java.lang.String classNames[])
          Creates the confusion matrix with the given class names.
Parameters:
classNames - an array containing the names the classes.

Method Detail

 o makeWeighted
public ConfusionMatrix makeWeighted(CostMatrix costs) throws java.lang.Exception
          Makes a copy of this ConfusionMatrix after applying the supplied CostMatrix to the cells. The resulting ConfusionMatrix can be used to get cost-weighted statistics.
Parameters:
costs - the CostMatrix.
Returns:
a ConfusionMatrix that has had costs applied.
Throws:
java.lang.Exception - if the CostMatrix is not of the same size as this ConfusionMatrix.
 o clone
public java.lang.Object clone() throws java.lang.CloneNotSupportedException
          Creates and returns a clone of this object.
Returns:
a clone of this instance.
Throws:
java.lang.CloneNotSupportedException - if an error occurs
Overrides:
clone in class Matrix
 o size
public int size()
          Gets the number of classes.
Returns:
the number of classes
 o className
public java.lang.String className(int index)
          Gets the name of one of the classes.
Parameters:
index - the index of the class.
Returns:
the class name.
 o addPrediction
public void addPrediction(NominalPrediction pred) throws java.lang.Exception
          Includes a prediction in the confusion matrix.
Parameters:
pred - the NominalPrediction to include
Throws:
java.lang.Exception - if no valid prediction was made (i.e. unclassified).
 o addPredictions
public void addPredictions(FastVector predictions) throws java.lang.Exception
          Includes a whole bunch of predictions in the confusion matrix.
Parameters:
predictions - a FastVector containing the NominalPredictions to include
Throws:
java.lang.Exception - if no valid prediction was made (i.e. unclassified).
 o getTwoClassStats
public TwoClassStats getTwoClassStats(int classIndex)
          Gets the performance with respect to one of the classes as a TwoClassStats object.
Parameters:
classIndex - the index of the class of interest.
Returns:
the generated TwoClassStats object.
 o correct
public double correct()
          Gets the number of correct classifications (that is, for which a correct prediction was made). (Actually the sum of the weights of these classifications)
Returns:
the number of correct classifications
 o incorrect
public double incorrect()
          Gets the number of incorrect classifications (that is, for which an incorrect prediction was made). (Actually the sum of the weights of these classifications)
Returns:
the number of incorrect classifications
 o total
public double total()
          Gets the number of predictions that were made (actually the sum of the weights of predictions where the class value was known).
Returns:
the number of predictions with known class
 o errorRate
public double errorRate()
          Returns the estimated error rate.
Returns:
the estimated error rate (between 0 and 1).
 o toString
public java.lang.String toString()
          Calls toString() with a default title.
Returns:
the confusion matrix as a string
Overrides:
toString in class Matrix
 o toString
public java.lang.String toString(java.lang.String title)
          Outputs the performance statistics as a classification confusion matrix. For each class value, shows the distribution of predicted class values.
Parameters:
title - the title for the confusion matrix
Returns:
the confusion matrix as a String

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