com.rapidminer.operator.performance
Class RankCorrelation

java.lang.Object
  com.rapidminer.operator.AbstractIOObject
      com.rapidminer.operator.ResultObjectAdapter
          com.rapidminer.tools.math.Averagable
              com.rapidminer.operator.performance.PerformanceCriterion
                  com.rapidminer.operator.performance.MeasuredPerformance
                      com.rapidminer.operator.performance.RankCorrelation

All Implemented Interfaces:

IOObject, ResultObject, Readable, Reportable, LoggingHandler, java.io.Serializable, java.lang.Cloneable, java.lang.Comparable<PerformanceCriterion>

public class RankCorrelation
extends MeasuredPerformance

Computes either the Spearman (rho) or Kendall (tau-b) rank correlation between the actual label and predicted values of an example set. Since ranking is involved, neither correlation is averageable.

Author:

Paul Rubin

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class com.rapidminer.operator.AbstractIOObject

AbstractIOObject.InputStreamProvider

Field Summary

static java.lang.String[]	DESCRIPTIONS
static java.lang.String[]	NAMES
static int	RHO
static int	TAU

Constructor Summary

RankCorrelation()
Default constructor

RankCorrelation(int type)
Constructor with user-specified choice of correlation coefficient.

RankCorrelation(RankCorrelation rc)

Method Summary

protected void	buildSingleAverage(Averagable averagable) Averaging across instances of RankCorrelation is unsupported (?)
void	countExample(Example example) Does nothing.
java.lang.String	getDescription() Returns a description of the performance criterion.
double	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	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.
void	startCounting(ExampleSet eSet, boolean useExampleWeights) Computes whichever of rho and tau was requested.

Methods inherited from class com.rapidminer.operator.performance.MeasuredPerformance

startCounting

Methods inherited from class com.rapidminer.operator.performance.PerformanceCriterion

compareTo, getMaxFitness

Methods inherited from class com.rapidminer.tools.math.Averagable

buildAverage, clone, cloneAveragable, formatPercent, getAverage, getAverageCount, getExtension, getFileDescription, getMakroAverage, getMakroStandardDeviation, getMakroVariance, getMikroStandardDeviation, getStandardDeviation, getVariance, isInTargetEncoding, setAverageCount, toString

Methods inherited from class com.rapidminer.operator.ResultObjectAdapter

addAction, getActions, getAnnotations, getResultIcon, log, log, logError, logNote, logWarning, toHTML, toResultString

Methods inherited from class com.rapidminer.operator.AbstractIOObject

appendOperatorToHistory, copy, getLog, getProcessingHistory, getSource, initWriting, read, read, read, read, setLoggingHandler, setSource, write

Methods inherited from class java.lang.Object

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

Methods inherited from interface com.rapidminer.operator.IOObject

appendOperatorToHistory, copy, getLog, getProcessingHistory, getSource, setLoggingHandler, setSource, write

Field Detail

NAMES

public static final java.lang.String[] NAMES

DESCRIPTIONS

public static final java.lang.String[] DESCRIPTIONS

RHO

public static final int RHO

See Also:

Constant Field Values

TAU

public static final int TAU

See Also:

Constant Field Values

Constructor Detail

RankCorrelation

public RankCorrelation()

Default constructor

RankCorrelation

public RankCorrelation(int type)

Constructor with user-specified choice of correlation coefficient. User specifies RHO or TAU.

Parameters:

type - coefficient type with coefficient choice

RankCorrelation

public RankCorrelation(RankCorrelation rc)

Method Detail

countExample

public void countExample(Example example)

Does nothing. Everything is done in startCounting(ExampleSet, boolean).

Specified by:

countExample in class MeasuredPerformance

getDescription

public java.lang.String getDescription()

Description copied from class: PerformanceCriterion

Returns a description of the performance criterion. This description is used for GUI purposes and automatic parameter type creation for the PerformanceEvaluator operator.

Specified by:

getDescription in class PerformanceCriterion

getExampleCount

public double getExampleCount()

Description copied from class: PerformanceCriterion

Returns the number of data points which was used to determine the criterion value. If the criterion does not use example weights (or no weight was given) then the returned value will be an integer. Otherwise, the returned value is the sum of all example weights.

Specified by:

getExampleCount in class PerformanceCriterion

getFitness

public double getFitness()

Description copied from class: PerformanceCriterion

Returns the fitness depending on the value. The fitness values will be used for all optimization purposes (feature space transformations, parameter optimizations...) and must always be maximized. Hence, if your criterion is better the smaller the value is you should return something like (-1 * value) or (1 / value).

Subclasses should use Averagable.getAverage() instead of Averagable.getMikroAverage() in this method since usually the makro average (if available) 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 but this is automatically done returned by Averagable.getAverage() in these cases.

Specified by:

getFitness in class PerformanceCriterion

buildSingleAverage

protected void buildSingleAverage(Averagable averagable)

Averaging across instances of RankCorrelation is unsupported (?) For now just build the usual average by summing up the values...

Specified by:

buildSingleAverage in class Averagable

getMikroAverage

public double getMikroAverage()

Description copied from class: Averagable

Returns the (current) value of the averagable (the average itself). If the method Averagable.buildSingleAverage(Averagable) was used, this method must return the micro average from both (or more) criteria. This is usually achieved by correctly implementing Averagable.buildSingleAverage(Averagable).

Specified by:

getMikroAverage in class Averagable

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. The returned string should only contain lowercase letters and underscore (RapidMiner parameter format) since the names will be automatically used for GUI purposes.

Specified by:

getName in interface ResultObject

Specified by:

getName in class Averagable

startCounting

public void startCounting(ExampleSet eSet,
                          boolean useExampleWeights)
                   throws OperatorException

Computes whichever of rho and tau was requested.

Overrides:

startCounting in class MeasuredPerformance

Throws:

OperatorException