icb-stats API icb-stats-31 (20120309094430)

edu.cornell.med.icb.stat
Class RootMeanSquaredErrorCalculator

java.lang.Object
  extended by edu.cornell.med.icb.stat.PredictionStatisticCalculator
      extended by edu.cornell.med.icb.stat.RootMeanSquaredErrorCalculator

public class RootMeanSquaredErrorCalculator
extends PredictionStatisticCalculator

Calculates the root mean squared error (RMSE). This measure is independent of any threshold. The RMSE should be used only for regression, when the decision value is expected to be on the same scale as the label.

See definition at http://cran.r-project.org/web/packages/ROCR/ROCR.pdf.

Author:
Fabien Campagne Date: Oct 9, 2009 Time: 3:44:20 PM

Field Summary
 
Fields inherited from class edu.cornell.med.icb.stat.PredictionStatisticCalculator
highestStatisticIsBest, optimalThreshold, statistic, zero
 
Constructor Summary
RootMeanSquaredErrorCalculator()
           
 
Method Summary
 double evaluateStatisticAtThreshold(double threshold, double[] decisionValues, double[] labels)
          Evaluate the statistic for a given decision function threshold.
 String getMeasureName()
           
 double thresholdIndependentStatistic(double[] decisionValues, double[] labels)
          Calculates the Matthews Correlation coefficient.
 double thresholdIndependentStatistic(ObjectList<double[]> decisionValueList, ObjectList<double[]> labelList)
          Calculates the optimal statistic at any decision threshold.
 
Methods inherited from class edu.cornell.med.icb.stat.PredictionStatisticCalculator
evaluateContingencyTable, evaluateStatisticAtThreshold, predictivePotential, thresholdIndependentStatisticStd, thresholdIndependentStatisticSte
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

RootMeanSquaredErrorCalculator

public RootMeanSquaredErrorCalculator()
Method Detail

getMeasureName

public String getMeasureName()
Specified by:
getMeasureName in class PredictionStatisticCalculator

evaluateStatisticAtThreshold

public double evaluateStatisticAtThreshold(double threshold,
                                           double[] decisionValues,
                                           double[] labels)
Description copied from class: PredictionStatisticCalculator
Evaluate the statistic for a given decision function threshold.

Specified by:
evaluateStatisticAtThreshold in class PredictionStatisticCalculator

thresholdIndependentStatistic

public double thresholdIndependentStatistic(double[] decisionValues,
                                            double[] labels)
Description copied from class: PredictionStatisticCalculator
Calculates the Matthews Correlation coefficient. Find the maximal MCC value irrespective of the threshold on the decision value. All the possible thresholds on the decision value are scanned and the maximum MCC values found is returned.

Overrides:
thresholdIndependentStatistic in class PredictionStatisticCalculator
Returns:

thresholdIndependentStatistic

public double thresholdIndependentStatistic(ObjectList<double[]> decisionValueList,
                                            ObjectList<double[]> labelList)
Description copied from class: PredictionStatisticCalculator
Calculates the optimal statistic at any decision threshold. All the possible thresholds on the decision value are scanned and the optimal statistic found is returned. When highestStatisticIsBest is true, the largest statistic found at any threshold is returned. Otherwise, the lowest statistic is returned.

Overrides:
thresholdIndependentStatistic in class PredictionStatisticCalculator
Parameters:
decisionValueList - Each element of this list should corresponds to a split of evaluation (decision values).
labelList - Each element of this list should corresponds to a split of evaluation (true labels).
Returns:

icb-stats API icb-stats-31 (20120309094430)

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