Package edu.cmu.tetrad.algcomparison.statistic

Class F1Arrow

java.lang.Object
edu.cmu.tetrad.algcomparison.statistic.F1Arrow
All Implemented Interfaces:
Statistic, Serializable
public class F1Arrow extends Object implements Statistic
Calculates the F1 statistic for arrowheads. See

...

We use what's on this page called the "traditional" F1 statistic. If the true contains X*->Y and estimated graph either does not contain an edge from X to Y or else does not contain an arrowhead at X for an edge from X to Y, one false positive is counted. Similarly for false negatives

Version:
$Id: $Id
Author:
Joseh Ramsey
See Also:

  • Constructor Details

    • F1Arrow

      public F1Arrow()
      Constructs a new instance of the algorithm.

  • Method Details

    • getAbbreviation

      public String getAbbreviation()
      The abbreviation for the statistic. This will be printed at the top of each column.
      Specified by:
      getAbbreviation in interface Statistic
      Returns:
      This abbreviation.

    • getDescription

      public String getDescription()
      Returns a short one-line description of this statistic. This will be printed at the beginning of the report.
      Specified by:
      getDescription in interface Statistic
      Returns:
      This description.

    • getValue

      public double getValue(Graph trueGraph, Graph estGraph, DataModel dataModel, Parameters parameters)
      Returns the value of this 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 (can be null).
      parameters - The parameters (can be null).
      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.