Package edu.cmu.tetrad.algcomparison.statistic

Class AdjacencyFn

java.lang.Object

edu.cmu.tetrad.algcomparison.statistic.AdjacencyFn

All Implemented Interfaces:

Statistic, Serializable

public class AdjacencyFn
extends Object
implements Statistic

The adjacency precision. The true positives are the number of adjacencies in both the true and estimated graphs.

Author:

josephramsey

See Also:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
AdjacencyFn()	Constructs the statistic.

Method Summary

Modifier and Type	Method	Description
String	getAbbreviation()	Returns the name of the statistic.
String	getDescription()	Returns the description of the statistic.
double	getNormValue(double value)	Returns a mapping of the statistic to the interval [0, 1], with higher being better.
double	getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of the statistic, given the true graph and the estimated graph.

Methods inherited from class java.lang.Object

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

Constructor Details

AdjacencyFn

public AdjacencyFn()

Constructs the statistic.

Method Details

getAbbreviation

public String getAbbreviation()

Returns the name of the statistic.

Specified by:

getAbbreviation in interface Statistic

Returns:

The name.

getDescription

public String getDescription()

Returns the description of the statistic.

Specified by:

getDescription in interface Statistic

Returns:

The description.

getValue

public double getValue(Graph trueGraph,
 Graph estGraph,
 DataModel dataModel)

Returns the value of the statistic, given the true graph and the estimated graph.

Specified by:

getValue in interface Statistic

Parameters:

trueGraph - The true graph (DAG, CPDAG, PAG_of_the_true_DAG).

estGraph - The estimated graph (same type).

dataModel - The data model.

Returns:

The value of the statistic.

getNormValue

public double getNormValue(double value)

Returns a mapping of the statistic to the interval [0, 1], with higher being better. This is used for a calculation of a utility for an algorithm.If the statistic is already between 0 and 1, you can just return the statistic.

Specified by:

getNormValue in interface Statistic

Parameters:

value - The value of the statistic.

Returns:

The weight of the statistic, 0 to 1, higher is better.