com.rapidminer.operator.learner.igss.utility
Class Coverage

java.lang.Object
  com.rapidminer.operator.learner.igss.utility.AbstractUtility
      com.rapidminer.operator.learner.igss.utility.InstanceAveraging
          com.rapidminer.operator.learner.igss.utility.Coverage

All Implemented Interfaces:

Utility

public class Coverage
extends InstanceAveraging

The instance-averaging utility function Coverage.

Author:

Dirk Dach

Field Summary

Fields inherited from class com.rapidminer.operator.learner.igss.utility.AbstractUtility

large, priors

Fields inherited from interface com.rapidminer.operator.learner.igss.utility.Utility

FIRST_TYPE_INDEX, LAST_TYPE_INDEX, TYPE_ACCURACY, TYPE_BINOMIAL, TYPE_LINEAR, TYPE_SQUARED, TYPE_WRACC, UTILITY_TYPES

Constructor Summary

Coverage(double[] priors, int large)
Constructs a new Coverage with the given default probability.

Method Summary

double	getUpperBound(double totalWeight, double totalPositiveWeight, Hypothesis hypo, double delta) Returns an upper bound for the utility of refinements for the given hypothesis.
double	utility(double totalWeight, double totalPositiveWeight, Hypothesis hypo) Calculates the utility for the given number of examples,positive examples and hypothesis.
double	variance(double totalWeight, double totalPositiveWeight, Hypothesis hypo) Calculates the empirical variance.

Methods inherited from class com.rapidminer.operator.learner.igss.utility.InstanceAveraging

conf, conf, confidenceIntervall, confSmallM

Methods inherited from class com.rapidminer.operator.learner.igss.utility.AbstractUtility

calculateM, confidenceIntervall, inverseNormal

Methods inherited from class java.lang.Object

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

Constructor Detail

Coverage

public Coverage(double[] priors,
                int large)

Constructs a new Coverage with the given default probability.

Method Detail

utility

public double utility(double totalWeight,
                      double totalPositiveWeight,
                      Hypothesis hypo)

Calculates the utility for the given number of examples,positive examples and hypothesis.

variance

public double variance(double totalWeight,
                       double totalPositiveWeight,
                       Hypothesis hypo)

Calculates the empirical variance.

Specified by:

variance in class InstanceAveraging

getUpperBound

public double getUpperBound(double totalWeight,
                            double totalPositiveWeight,
                            Hypothesis hypo,
                            double delta)

Returns an upper bound for the utility of refinements for the given hypothesis.