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## de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures
Class BTExplainingAwayResidual

    java.lang.Object
      de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
          de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual

All Implemented Interfaces:
  InstantiableFromParameterSet, Storable, Cloneable

    public class BTExplainingAwayResidual

extends Measure

Structure learning `Measure` that computes a maximum spanning tree based on the explaining away residual and uses the resulting tree structure as structure of a Bayesian tree (special case of a Bayesian network) in a `BayesianNetworkScoringFunction`.

Author:
  Jan Grau

Nested Class Summary
`static class` | `BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet` Class for the parameters of a `BTExplainingAwayResidual` structure `Measure`.

Constructor Summary
`BTExplainingAwayResidual(BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet parameters)` Creates a new `BTExplainingAwayResidual` from the corresponding `InstanceParameterSet` `parameters/code>.`
`BTExplainingAwayResidual(double[] ess)` Creates a new explaining away residual Bayesian tree `Measure`.
`BTExplainingAwayResidual(StringBuffer buf)` Re-creates a `BTExplainingAwayResidual` from is XML-representation as returned by `toXML()`.

Method Summary
`BTExplainingAwayResidual` | `clone()`
`InstanceParameterSet` | `getCurrentParameterSet()` Returns the `InstanceParameterSet` that has been used to instantiate the current instance of the implementing class.
`String` | `getInstanceName()` Returns the name of the `Measure` and possibly some additional information about the current instance.
`int[][]` | `getParents(Sample fg, Sample bg, double[] weightsFg, double[] weightsBg, int length)` Returns the optimal parents for the given data and weights.
`StringBuffer` | `toXML()` This method returns an XML-representation of an instance of the implementing class.

Methods inherited from class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
`fillTensor, fillTensor, getCMI, getCMI, getEAR, getEAR, getMI, getMI, getStatistics, getStatisticsOrderTwo, isShiftable, sum, toParents, union`

Methods inherited from class java.lang.Object
`equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

### BTExplainingAwayResidual

    public BTExplainingAwayResidual(double[] ess)

  Creates a new explaining away residual Bayesian tree `Measure`.

  Parameters:
    `ess` - the equivalent sample sizes for the classes

### BTExplainingAwayResidual

    public BTExplainingAwayResidual(BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet parameters)

  Creates a new `BTExplainingAwayResidual` from the corresponding `InstanceParameterSet` `parameters/code>.

  Parameters:
    `parameters` - the parameters
  `

### BTExplainingAwayResidual

    public BTExplainingAwayResidual(StringBuffer buf)
                             throws NonParsableException

  Re-creates a `BTExplainingAwayResidual` from is XML-representation as returned by `toXML()`.

  Parameters:
    `buf` - the XML-representation
  Throws:
    `NonParsableException` - is thrown if the XML-code could not be parsed

Method Detail

### clone

    public BTExplainingAwayResidual clone()
                                   throws CloneNotSupportedException

  Overrides:
    `clone` in class `Measure`
  Throws:
    `CloneNotSupportedException`

### getInstanceName

    public String getInstanceName()

  Description copied from class: `Measure`
  Returns the name of the `Measure` and possibly some additional information about the current instance.

  Specified by:
    `getInstanceName` in class `Measure`
  Returns:
    the name

### getParents

    public int[][] getParents(Sample fg,
                              Sample bg,
                              double[] weightsFg,
                              double[] weightsBg,
                              int length)
                       throws Exception

  Description copied from class: `Measure`
  Returns the optimal parents for the given data and weights. The array of parents `p` at each position `i` is build as follows:
  - `p[i][p.length - 1]` contains the index `i` itself
  - `p[i][p.length - 2]` contains the "most important" parent
  - ...
  - `p[i][0]` contains the "least important parent

  Specified by:
    `getParents` in class `Measure`
  Parameters:
    `fg` - the data of the current (foreground) class
    `bg` - the data of the negative (background) class
    `weightsFg` - the weights for the sequences of `fg`
    `weightsBg` - the weights for the sequences of `bg`
    `length` - the length of the model, must be equal to the length of the sequences
  Returns:
    the parents
  Throws:
    `Exception` - thrown if the lengths do not match or other problems concerning the data occur

### toXML

    public StringBuffer toXML()

  Description copied from interface: `Storable`
  This method returns an XML-representation of an instance of the implementing class.

  Returns:
    the XML-representation

### getCurrentParameterSet

    public InstanceParameterSet getCurrentParameterSet()
                                                throws Exception

  Description copied from interface: `InstantiableFromParameterSet`
  Returns the `InstanceParameterSet` that has been used to instantiate the current instance of the implementing class. If the current instance was not created using a `InstanceParameterSet`, an equivalent `InstanceParameterSet` should be returned, such that an instance created using this `InstanceParameterSet` would be in principle equal to the current instance.

  Returns:
    the current `InstanceParameterSet`
  Throws:
    `Exception` - is thrown if the `InstanceParameterSet` could not be returned

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