edu.udo.cs.yale.operator.performance
Class BinaryClassificationPerformance

java.lang.Object
  edu.udo.cs.yale.operator.AbstractIOObject
      edu.udo.cs.yale.operator.ResultObjectAdapter
          edu.udo.cs.yale.tools.math.Averagable
              edu.udo.cs.yale.operator.performance.PerformanceCriterion
                  edu.udo.cs.yale.operator.performance.MeasuredPerformance
                      edu.udo.cs.yale.operator.performance.BinaryClassificationPerformance

All Implemented Interfaces:

IOObject, ResultObject, java.lang.Cloneable, java.lang.Comparable<Averagable>

public class BinaryClassificationPerformance
extends MeasuredPerformance

This class encapsulates the well known binary classification criteria precision and recall. Furthermore it can be used to calculate the fallout, the equally weighted f-measure (f1-measure), the lift, and the values for TRUE_POSITIVE, FALSE_POSITIVE, TRUE_NEGATIVE, and FALSE_NEGATIVE. With "positive" we refer to the first class and with "negative" we refer to the second.

Version:

$Id: BinaryClassificationPerformance.java,v 2.14 2006/03/21 15:35:50 ingomierswa Exp $

Author:

Ingo Mierswa, Simon Fischer

Field Summary

private int[][]	counter true label, predicted label.
static java.lang.String[]	DESCRIPTION
static int	F_MEASURE
static int	FALLOUT
static int	FALSE_NEGATIVE
static int	FALSE_POSITIVE
static int	LIFT
static java.lang.String[]	NAME
private int	negative
private static int	NEGATIVE
private java.lang.String	negativeClassName Name of the negative class.
private static int	POSITIVE
private java.lang.String	positiveClassName Name of the positive class.
static int	PRECISION
static int	RECALL
static int	TRUE_NEGATIVE
static int	TRUE_POSITIVE
private int	type

Constructor Summary

BinaryClassificationPerformance()

BinaryClassificationPerformance(int type)

BinaryClassificationPerformance(int type, int negative)

BinaryClassificationPerformance(int type, int[][] counter)
For test cases only.

Method Summary

void	buildSingleAverage(Averagable performance) This method should build the average of this and another averagables of the same type.
protected void	cloneAveragable(Averagable newPC) Must be implemented by subclasses such that it copies all values of other to this.
void	countExample(Example example) Counts a single example, e.g. by summing up errors.
boolean	formatPercent() Indicates wether or not percentage format should be used in the Averagable.toString() method.
java.lang.String	getDescription() Returns a description of the performance criterion.
int	getExampleCount() Returns the number of data points which was used to determine the criterion value.
double	getFitness() Returns the fitness depending on the value.
double	getMaxFitness() Returns the maximum fitness.
double	getMikroAverage() Returns the (current) value of the averagable (the average itself).
double	getMikroVariance() Returns the variance of the averagable.
java.lang.String	getName() Returns the name of this averagable.
static BinaryClassificationPerformance	newInstance(java.lang.String name)
void	readCriterionData(java.io.BufferedReader in) Reads the performance data from the given reader.
void	startCounting(ExampleSet eSet) Initialises the criterion.
java.lang.String	toHTML() Returns a HTML table for the confusion matrix.
java.lang.String	toString()
void	writeCriterionData(java.io.PrintWriter out) Writes the performance criterion into the given writer.

Methods inherited from class edu.udo.cs.yale.operator.performance.PerformanceCriterion

compareTo, readPerformanceCriterion, writePerformanceCriterion

Methods inherited from class edu.udo.cs.yale.tools.math.Averagable

buildAverage, clone, formatDeviation, formatValue, getAverage, getMakroAverage, getMakroStandardDeviation, getMakroVariance, getMikroStandardDeviation, getStandardDeviation, getVariance

Methods inherited from class edu.udo.cs.yale.operator.ResultObjectAdapter

addAction, getActions, getVisualisationComponent, toHTML, toResultString

Methods inherited from class edu.udo.cs.yale.operator.AbstractIOObject

copy, read, read, read, write, write

Methods inherited from class java.lang.Object

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

Methods inherited from interface edu.udo.cs.yale.operator.IOObject

copy, write, write

Field Detail

PRECISION

public static final int PRECISION

See Also:

Constant Field Values

RECALL

public static final int RECALL

See Also:

Constant Field Values

LIFT

public static final int LIFT

See Also:

Constant Field Values

FALLOUT

public static final int FALLOUT

See Also:

Constant Field Values

F_MEASURE

public static final int F_MEASURE

See Also:

Constant Field Values

FALSE_POSITIVE

public static final int FALSE_POSITIVE

See Also:

Constant Field Values

FALSE_NEGATIVE

public static final int FALSE_NEGATIVE

See Also:

Constant Field Values

TRUE_POSITIVE

public static final int TRUE_POSITIVE

See Also:

Constant Field Values

TRUE_NEGATIVE

public static final int TRUE_NEGATIVE

See Also:

Constant Field Values

NEGATIVE

private static final int NEGATIVE

See Also:

Constant Field Values

POSITIVE

private static final int POSITIVE

See Also:

Constant Field Values

NAME

public static final java.lang.String[] NAME

DESCRIPTION

public static final java.lang.String[] DESCRIPTION

type

private int type

negative

private int negative

counter

private int[][] counter

true label, predicted label. PP = TP, PN = FN, NP = FP, NN = TN.

positiveClassName

private java.lang.String positiveClassName

Name of the positive class.

negativeClassName

private java.lang.String negativeClassName

Name of the negative class.

Constructor Detail

BinaryClassificationPerformance

public BinaryClassificationPerformance()

BinaryClassificationPerformance

public BinaryClassificationPerformance(int type)

BinaryClassificationPerformance

public BinaryClassificationPerformance(int type,
                                       int negative)

BinaryClassificationPerformance

public BinaryClassificationPerformance(int type,
                                       int[][] counter)

For test cases only.

Method Detail

newInstance

public static BinaryClassificationPerformance newInstance(java.lang.String name)

writeCriterionData

public void writeCriterionData(java.io.PrintWriter out)
                        throws java.io.IOException

Description copied from class: PerformanceCriterion

Writes the performance criterion into the given writer. Please note that the criterion must be written in a human readable format!

Specified by:

writeCriterionData in class PerformanceCriterion

Throws:

java.io.IOException

readCriterionData

public void readCriterionData(java.io.BufferedReader in)
                       throws java.io.IOException

Description copied from class: PerformanceCriterion

Reads the performance data from the given reader.

Specified by:

readCriterionData in class PerformanceCriterion

Throws:

java.io.IOException

getExampleCount

public int getExampleCount()

Description copied from class: PerformanceCriterion

Returns the number of data points which was used to determine the criterion value.

Specified by:

getExampleCount in class PerformanceCriterion

startCounting

public void startCounting(ExampleSet eSet)
                   throws OperatorException

Description copied from class: MeasuredPerformance

Initialises the criterion. The default implementation does nothing.

Overrides:

startCounting in class MeasuredPerformance

Throws:

OperatorException

countExample

public void countExample(Example example)

Description copied from class: MeasuredPerformance

Counts a single example, e.g. by summing up errors.

Specified by:

countExample in class MeasuredPerformance

getMikroAverage

public double getMikroAverage()

Description copied from class: Averagable

Returns the (current) value of the averagable (the average itself).

Specified by:

getMikroAverage in class Averagable

getFitness

public double getFitness()

Description copied from class: PerformanceCriterion

Returns the fitness depending on the value. Subclasses should use getAverage() instead of getValue() in this method since usually the makro average should be optmized instead of the mikro average. The mikro average should only be used in the (rare) cases where no makro average is available.

Specified by:

getFitness in class PerformanceCriterion

getMaxFitness

public double getMaxFitness()

Description copied from class: PerformanceCriterion

Returns the maximum fitness. The default implementation resturns POSITIVE_INFINITY, subclasses may override this to allow feature operators to end the optimization if the maximum was reached.

Overrides:

getMaxFitness in class PerformanceCriterion

getMikroVariance

public double getMikroVariance()

Description copied from class: Averagable

Returns the variance of the averagable. The returned value must not be negative. If the averagable does not define a variance this method should return Double.NaN.

Specified by:

getMikroVariance in class Averagable

getName

public java.lang.String getName()

Description copied from class: Averagable

Returns the name of this averagable.

Specified by:

getName in interface ResultObject

Specified by:

getName in class Averagable

getDescription

public java.lang.String getDescription()

Description copied from class: MeasuredPerformance

Returns a description of the performance criterion.

Specified by:

getDescription in class MeasuredPerformance

formatPercent

public boolean formatPercent()

Description copied from class: Averagable

Indicates wether or not percentage format should be used in the Averagable.toString() method. The default implementation returns false.

Overrides:

formatPercent in class Averagable

cloneAveragable

protected void cloneAveragable(Averagable newPC)

Description copied from class: Averagable

Must be implemented by subclasses such that it copies all values of other to this. When this method is called, it is guaranteed, that other is a subclass of the class of the object it is called on.

Specified by:

cloneAveragable in class Averagable

buildSingleAverage

public void buildSingleAverage(Averagable performance)

Description copied from class: Averagable

This method should build the average of this and another averagables of the same type. The next invocation of getValue() should return the average of this and the given averagable. Please refer to SimpleCriterion for a simple implementation example.

Specified by:

buildSingleAverage in class Averagable

toString

public java.lang.String toString()

Overrides:

toString in class Averagable

toHTML

public java.lang.String toHTML()

Returns a HTML table for the confusion matrix.

Overrides:

toHTML in class Averagable