Uses of Class
gov.sandia.cognition.statistics.method.ReceiverOperatingCharacteristic

Packages that use ReceiverOperatingCharacteristic
gov.sandia.cognition.statistics.method Provides algorithms for evaluating statistical data and conducting statistical inference, particularly frequentist methods. 
 

Uses of ReceiverOperatingCharacteristic in gov.sandia.cognition.statistics.method
 

Methods in gov.sandia.cognition.statistics.method that return ReceiverOperatingCharacteristic
 ReceiverOperatingCharacteristic ReceiverOperatingCharacteristic.clone()
           
static ReceiverOperatingCharacteristic ReceiverOperatingCharacteristic.create(Collection<? extends InputOutputPair<Double,Boolean>> data)
          Creates an ROC curve based on the scored data with target information
static ReceiverOperatingCharacteristic ReceiverOperatingCharacteristic.createFromTargetEstimatePairs(Collection<? extends Pair<Boolean,? extends Number>> data)
          Creates an ROC curve based on the scored data with target information.
 

Methods in gov.sandia.cognition.statistics.method with parameters of type ReceiverOperatingCharacteristic
static double ReceiverOperatingCharacteristic.Statistic.computeAreaUnderCurve(ReceiverOperatingCharacteristic roc)
          Computes the "pessimistic" area under the ROC curve using the top-left rectangle method for numerical integration.
static ConvexReceiverOperatingCharacteristic ConvexReceiverOperatingCharacteristic.computeConvexNull(ReceiverOperatingCharacteristic roc)
          Computes the convex hull of a ROC curve
static ReceiverOperatingCharacteristic.DataPoint ReceiverOperatingCharacteristic.Statistic.computeOptimalThreshold(ReceiverOperatingCharacteristic roc)
          Determines the DataPoint, and associated threshold, that simultaneously maximizes the value of Area=TruePositiveRate+TrueNegativeRate, usually the upper-left "knee" on the ROC curve.
static ReceiverOperatingCharacteristic.DataPoint ReceiverOperatingCharacteristic.Statistic.computeOptimalThreshold(ReceiverOperatingCharacteristic roc, double truePositiveWeight, double trueNegativeWeight)
          Determines the DataPoint, and associated threshold, that simultaneously maximizes the value of Area=TruePositiveRate+TrueNegativeRate, usually the upper-left "knee" on the ROC curve.
 

Constructors in gov.sandia.cognition.statistics.method with parameters of type ReceiverOperatingCharacteristic
ReceiverOperatingCharacteristic.Statistic(ReceiverOperatingCharacteristic roc)
          Creates a new instance of Statistic