All Packages Class Hierarchy This Package Previous Next Index WEKA's home
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)
ConfusionMatrix(String[])
- Creates the confusion matrix with the given class names.
addPrediction(NominalPrediction)
- Includes a prediction in the confusion matrix.
addPredictions(FastVector)
- Includes a whole bunch of predictions in the confusion matrix.
className(int)
- Gets the name of one of the classes.
clone()
- Creates and returns a clone of this object.
correct()
- Gets the number of correct classifications (that is, for which a
correct prediction was made).
errorRate()
- Returns the estimated error rate.
getTwoClassStats(int)
- Gets the performance with respect to one of the classes
as a TwoClassStats object.
incorrect()
- Gets the number of incorrect classifications (that is, for which an
incorrect prediction was made).
makeWeighted(CostMatrix)
- Makes a copy of this ConfusionMatrix after applying the
supplied CostMatrix to the cells.
size()
- Gets the number of classes.
toString()
- Calls toString() with a default title.
toString(String)
- Outputs the performance statistics as a classification confusion
matrix.
total()
- Gets the number of predictions that were made
(actually the sum of the weights of predictions where the
class value was known).
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.
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.
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
size
public int size()
Gets the number of classes.
- Returns:
- the number of classes
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.
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).
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).
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.
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
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
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
errorRate
public double errorRate()
Returns the estimated error rate.
- Returns:
- the estimated error rate (between 0 and 1).
toString
public java.lang.String toString()
Calls toString() with a default title.
- Returns:
- the confusion matrix as a string
- Overrides:
- toString in class Matrix
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
All Packages Class Hierarchy This Package Previous Next Index WEKA's home