com.rapidminer.operator.performance
Class CorrelationCriterion

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.CorrelationCriterion

All Implemented Interfaces:

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

Direct Known Subclasses:

SquaredCorrelationCriterion

public class CorrelationCriterion
extends MeasuredPerformance

Computes the empirical corelation coefficient 'r' between label and prediction. For P=prediction, L=label, V=Variance, Cov=Covariance we calculate r by:
Cov(L,P) / sqrt(V(L)*V(P)). Implementation hint: this implementation intensionally recomputes the mean and variance of prediction and label despite the fact that they are available by the Attribute objects. The reason: it can happen, that there are some examples which have a NaN as prediction or label, but not both. In this case, mean and variance stored in tie Attributes and computed here can differ.

Author:

Robert Rudolph, Ingo Mierswa, Sebastian Land

See Also:

Serialized Form

Nested Class Summary

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

AbstractIOObject.InputStreamProvider

Constructor Summary

CorrelationCriterion()

CorrelationCriterion(CorrelationCriterion sc)

Method Summary

void	buildSingleAverage(Averagable performance) This method should build the average of this and another averagable of the same type.
void	countExample(Example example) Updates all sums needed to compute the correlation coefficient.
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	getMaxFitness() Returns the maximum fitness of 1.0.
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) Initializes the criterion.

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

startCounting

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

compareTo

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

Constructor Detail

CorrelationCriterion

public CorrelationCriterion()

CorrelationCriterion

public CorrelationCriterion(CorrelationCriterion sc)

Method Detail

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

getMaxFitness

public double getMaxFitness()

Returns the maximum fitness of 1.0.

Overrides:

getMaxFitness in class PerformanceCriterion

countExample

public void countExample(Example example)

Updates all sums needed to compute the correlation coefficient.

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

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

startCounting

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

Description copied from class: MeasuredPerformance

Initializes the criterion. The default implementation does nothing.

Overrides:

startCounting in class MeasuredPerformance

Throws:

OperatorException

buildSingleAverage

public void buildSingleAverage(Averagable performance)

Description copied from class: Averagable

This method should build the average of this and another averagable of the same type. The next invocation of Averagable.getMikroAverage() should return the average of this and the given averagable. Hence, this method is used to build the actual micro average value of two criteria. Please refer to SimpleCriterion for a simple implementation example.

Specified by:

buildSingleAverage in class Averagable

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

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