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 and Description
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(CLGaussian 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(Distribution 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.
static double	calculate(Table joint, LogarithmBase logarithmBase) Measures the uncertainty of a distribution.

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.