Package com.bayesserver.statistics

Class Entropy

java.lang.Object

com.bayesserver.statistics.Entropy

public final class Entropy
extends Object

Calculates entropy, joint entropy or conditional entropy, which can be used to determine the uncertainty in the states of a discrete distribution. A higher values indicates less certainty about being in a particular state.

Method Summary

Modifier and Type	Method	Description
static double	calculate(CLGaussian joint, LogarithmBase logarithmBase)	Measures the uncertainty of a distribution.
static double	calculate(CLGaussian joint, List<VariableContext> conditionOn, LogarithmBase logarithmBase)	Measures the uncertainty of a distribution conditional on one or more variables.
static double	calculate(Distribution joint, LogarithmBase logarithmBase)	Measures the uncertainty of a distribution.
static double	calculate(Distribution joint, List<VariableContext> conditionOn, LogarithmBase logarithmBase)	Measures the uncertainty of a distribution conditional on one or more variables.
static double	calculate(Table joint, LogarithmBase logarithmBase)	Measures the uncertainty of a distribution.
static double	calculate(Table joint, List<VariableContext> conditionOn, LogarithmBase logarithmBase)	Measures the uncertainty of a distribution conditional on one or more variables.

Methods inherited from class java.lang.Object

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

Method Detail

calculate

public static double calculate(Distribution joint,
                               LogarithmBase logarithmBase)

Measures the uncertainty of a distribution.

Parameters:

joint - The marginal or joint distribution.

logarithmBase - The logarithm base to use for the calculations.

Returns:

The entropy value.

calculate

public static double calculate(Distribution joint,
                               List<VariableContext> conditionOn,
                               LogarithmBase logarithmBase)

Measures the uncertainty of a distribution conditional on one or more variables.

Parameters:

joint - The marginal or joint distribution.

conditionOn - Any conditional variables. I.e. those on the right hand side of H(Y|X) when calculating conditional entropy.

logarithmBase - The logarithm base to use for the calculations.

Returns:

The entropy value.

calculate

public static double calculate(Table joint,
                               List<VariableContext> conditionOn,
                               LogarithmBase logarithmBase)

Measures the uncertainty of a distribution conditional on one or more variables.

Parameters:

joint - The marginal or joint distribution.

conditionOn - Any conditional variables. I.e. those on the right hand side of H(Y|X) when calculating conditional entropy.

logarithmBase - The logarithm base to use for the calculations.

Returns:

The entropy value.

calculate

public static double calculate(Table joint,
                               LogarithmBase logarithmBase)

Measures the uncertainty of a distribution.

Parameters:

joint - The marginal or joint distribution.

logarithmBase - The logarithm base to use for the calculations.

Returns:

The entropy value.

calculate

public static double calculate(CLGaussian joint,
                               List<VariableContext> conditionOn,
                               LogarithmBase logarithmBase)

Measures the uncertainty of a distribution conditional on one or more variables.

Parameters:

joint - The marginal or joint distribution.

conditionOn - Any conditional variables. I.e. those on the right hand side of H(Y|X) when calculating conditional entropy.

logarithmBase - The logarithm base to use for the calculations.

Returns:

The entropy value.

calculate

public static double calculate(CLGaussian joint,
                               LogarithmBase logarithmBase)

Measures the uncertainty of a distribution.

Parameters:

joint - The marginal or joint distribution.

logarithmBase - The logarithm base to use for the calculations.

Returns:

The entropy value.