icb-stats API icb-stats-31 (20120309094430)
A C E G H L M O P R S T Z

A

AccuracyCalculator - Class in edu.cornell.med.icb.stat
Calculates the accuracy of predictions.
AccuracyCalculator() - Constructor for class edu.cornell.med.icb.stat.AccuracyCalculator
 
addDataPoint(double, double) - Method in class edu.cornell.med.icb.stat.LinearRegression
Add a point to the linear regression calculation.
addDataPoints(double[], double[]) - Method in class edu.cornell.med.icb.stat.LinearRegression
Add a points to the linear regression calculation.
AreaUnderTheRocCurveCalculator - Class in edu.cornell.med.icb.stat
 
AreaUnderTheRocCurveCalculator() - Constructor for class edu.cornell.med.icb.stat.AreaUnderTheRocCurveCalculator
 

C

calculateStats() - Method in class edu.cornell.med.icb.stat.ZScoreCalculator
Calculate mean and std deviation of scores.
compute(double[], double[]) - Static method in class edu.cornell.med.icb.stat.MinMaxCalculator
 
compute(double[], double[], int) - Static method in class edu.cornell.med.icb.stat.MinMaxCalculator
Compute the min/max statistics.
count() - Method in class edu.cornell.med.icb.stat.ZScoreCalculator
 

E

edu.cornell.med.icb.stat - package edu.cornell.med.icb.stat
 
evaluateAccuracy(double, double[], double[]) - Method in class edu.cornell.med.icb.stat.AccuracyCalculator
Evaluate the accuracy for a given decision function threshold.
evaluateContingencyTable(double, double[], double[]) - Method in class edu.cornell.med.icb.stat.PredictionStatisticCalculator
Evaluate the contingency table at a specific threshold.
evaluateMCC(double, double[], double[]) - Method in class edu.cornell.med.icb.stat.MatthewsCorrelationCalculator
Evaluate the Mathews Correlation coefficient for a given decision function threshold.
evaluateSensitivity(double, double[], double[]) - Method in class edu.cornell.med.icb.stat.SensitivityCalculator
Evaluate the sensitivity of predictions at a given decision function threshold.
evaluateSpecificity(double, double[], double[]) - Method in class edu.cornell.med.icb.stat.SpecificityCalculator
Evaluate the specificity of predictions at a given decision function threshold.
evaluateStatistic(double[], double[]) - Method in class edu.cornell.med.icb.stat.AreaUnderTheRocCurveCalculator
 
evaluateStatisticAtThreshold(double, double[], double[]) - Method in class edu.cornell.med.icb.stat.AccuracyCalculator
 
evaluateStatisticAtThreshold(double, double[], double[]) - Method in class edu.cornell.med.icb.stat.AreaUnderTheRocCurveCalculator
 
evaluateStatisticAtThreshold(double, double[], double[]) - Method in class edu.cornell.med.icb.stat.MatthewsCorrelationCalculator
 
evaluateStatisticAtThreshold(double, ObjectList<double[]>, ObjectList<double[]>) - Method in class edu.cornell.med.icb.stat.PredictionStatisticCalculator
 
evaluateStatisticAtThreshold(double, double[], double[]) - Method in class edu.cornell.med.icb.stat.PredictionStatisticCalculator
Evaluate the statistic for a given decision function threshold.
evaluateStatisticAtThreshold(double, double[], double[]) - Method in class edu.cornell.med.icb.stat.RootMeanSquaredErrorCalculator
 
evaluateStatisticAtThreshold(double, double[], double[]) - Method in class edu.cornell.med.icb.stat.SensitivityCalculator
 
evaluateStatisticAtThreshold(double, double[], double[]) - Method in class edu.cornell.med.icb.stat.SpecificityCalculator
 

G

getCorrelationCoefficient() - Method in class edu.cornell.med.icb.stat.LinearRegression
Obtain the correlation coefficient.
getMeasureName() - Method in class edu.cornell.med.icb.stat.AccuracyCalculator
 
getMeasureName() - Method in class edu.cornell.med.icb.stat.AreaUnderTheRocCurveCalculator
 
getMeasureName() - Method in class edu.cornell.med.icb.stat.MatthewsCorrelationCalculator
 
getMeasureName() - Method in class edu.cornell.med.icb.stat.PredictionStatisticCalculator
 
getMeasureName() - Method in class edu.cornell.med.icb.stat.RootMeanSquaredErrorCalculator
 
getMeasureName() - Method in class edu.cornell.med.icb.stat.SensitivityCalculator
 
getMeasureName() - Method in class edu.cornell.med.icb.stat.SpecificityCalculator
 
getSlope() - Method in class edu.cornell.med.icb.stat.LinearRegression
Obtain the slope.
getXIntercept() - Method in class edu.cornell.med.icb.stat.LinearRegression
Obtain the x-intercept.
getYIntercept() - Method in class edu.cornell.med.icb.stat.LinearRegression
Obtain the y-intercept.

H

highestStatisticIsBest - Variable in class edu.cornell.med.icb.stat.PredictionStatisticCalculator
Indicates that a larger statistic represents a better predictor performance.

L

LinearRegression - Class in edu.cornell.med.icb.stat
This class performs a Linear Regression.
LinearRegression() - Constructor for class edu.cornell.med.icb.stat.LinearRegression
Create a linear regression calculator.
LOG - Static variable in class edu.cornell.med.icb.stat.MinMaxCalculator
The logger to use.

M

main(String[]) - Static method in class edu.cornell.med.icb.stat.MinMaxCalculator
 
MatthewsCorrelationCalculator - Class in edu.cornell.med.icb.stat
Calculates the Matthews Correlation coefficient.
MatthewsCorrelationCalculator() - Constructor for class edu.cornell.med.icb.stat.MatthewsCorrelationCalculator
 
max() - Method in class edu.cornell.med.icb.stat.ZScoreCalculator
 
mean() - Method in class edu.cornell.med.icb.stat.ZScoreCalculator
 
min() - Method in class edu.cornell.med.icb.stat.ZScoreCalculator
 
MinMaxCalculator - Class in edu.cornell.med.icb.stat
Calculates the Min/Max statistics for a feature.
MinMaxCalculator() - Constructor for class edu.cornell.med.icb.stat.MinMaxCalculator
 

O

observe(double) - Method in class edu.cornell.med.icb.stat.ZScoreCalculator
 
optimalThreshold - Variable in class edu.cornell.med.icb.stat.PredictionStatisticCalculator
The value of the threshold where the optimal statistic is obtained.

P

PredictionStatisticCalculator - Class in edu.cornell.med.icb.stat
 
PredictionStatisticCalculator() - Constructor for class edu.cornell.med.icb.stat.PredictionStatisticCalculator
 
predictivePotential(double) - Method in class edu.cornell.med.icb.stat.PredictionStatisticCalculator
Return a value that is larger when the statistics indicates a larger predictive potential.

R

regress() - Method in class edu.cornell.med.icb.stat.LinearRegression
Run the regression.
reset() - Method in class edu.cornell.med.icb.stat.LinearRegression
Prepare for a new regression calculation.
reset() - Method in class edu.cornell.med.icb.stat.ZScoreCalculator
Reset the calculator to a state before any value have been observed.
RootMeanSquaredErrorCalculator - Class in edu.cornell.med.icb.stat
Calculates the root mean squared error (RMSE).
RootMeanSquaredErrorCalculator() - Constructor for class edu.cornell.med.icb.stat.RootMeanSquaredErrorCalculator
 

S

SensitivityCalculator - Class in edu.cornell.med.icb.stat
Calculates the specificity of predictions.
SensitivityCalculator() - Constructor for class edu.cornell.med.icb.stat.SensitivityCalculator
 
SpecificityCalculator - Class in edu.cornell.med.icb.stat
Calculates the Matthews Correlation coefficient.
SpecificityCalculator() - Constructor for class edu.cornell.med.icb.stat.SpecificityCalculator
 
statistic - Variable in class edu.cornell.med.icb.stat.PredictionStatisticCalculator
The value of the statistic.
stdDev() - Method in class edu.cornell.med.icb.stat.ZScoreCalculator
 
sum() - Method in class edu.cornell.med.icb.stat.ZScoreCalculator
 

T

thresholdIndependentStatistic(double[], double[]) - Method in class edu.cornell.med.icb.stat.AreaUnderTheRocCurveCalculator
 
thresholdIndependentStatistic(ObjectList<double[]>, ObjectList<double[]>) - Method in class edu.cornell.med.icb.stat.AreaUnderTheRocCurveCalculator
Calculates the optimal statistic at any decision threshold.
thresholdIndependentStatistic(ObjectList<double[]>, ObjectList<double[]>) - Method in class edu.cornell.med.icb.stat.PredictionStatisticCalculator
Calculates the optimal statistic at any decision threshold.
thresholdIndependentStatistic(double[], double[]) - Method in class edu.cornell.med.icb.stat.PredictionStatisticCalculator
Calculates the Matthews Correlation coefficient.
thresholdIndependentStatistic(double[], double[]) - Method in class edu.cornell.med.icb.stat.RootMeanSquaredErrorCalculator
 
thresholdIndependentStatistic(ObjectList<double[]>, ObjectList<double[]>) - Method in class edu.cornell.med.icb.stat.RootMeanSquaredErrorCalculator
 
thresholdIndependentStatisticStd(ObjectList<double[]>, ObjectList<double[]>) - Method in class edu.cornell.med.icb.stat.AreaUnderTheRocCurveCalculator
 
thresholdIndependentStatisticStd(ObjectList<double[]>, ObjectList<double[]>) - Method in class edu.cornell.med.icb.stat.PredictionStatisticCalculator
 
thresholdIndependentStatisticSte(ObjectList<double[]>, ObjectList<double[]>) - Method in class edu.cornell.med.icb.stat.PredictionStatisticCalculator
Calculate the standard error of the mean of the statistic.

Z

zero - Variable in class edu.cornell.med.icb.stat.PredictionStatisticCalculator
This value indicates the value of the performance statistics that would be obtained if the prediction was completely random.
zScore(double) - Method in class edu.cornell.med.icb.stat.ZScoreCalculator
 
zScore(double, boolean) - Method in class edu.cornell.med.icb.stat.ZScoreCalculator
 
ZScoreCalculator - Class in edu.cornell.med.icb.stat
A helper class to calculate zScores for observations.
ZScoreCalculator() - Constructor for class edu.cornell.med.icb.stat.ZScoreCalculator
 

A C E G H L M O P R S T Z
icb-stats API icb-stats-31 (20120309094430)

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