EditableBayesNet

java.lang.Object
- weka.classifiers.Classifier
- - weka.classifiers.bayes.BayesNet
  - - weka.classifiers.bayes.net.EditableBayesNet

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, AdditionalMeasureProducer, CapabilitiesHandler, Drawable, OptionHandler, RevisionHandler, WeightedInstancesHandler

Direct Known Subclasses:

BayesNetGenerator
```
public class EditableBayesNet
extends BayesNet
```
Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier. Provides datastructures (network structure, conditional probability distributions, etc.) and facilities common to Bayes Network learning algorithms like K2 and B.

For more information see:

http://www.cs.waikato.ac.nz/~remco/weka.pdf
Valid options are:
```
 -D
  Do not use ADTree data structure
 
```
```
 -B <BIF file>
  BIF file to compare with
 
```
```
 -Q weka.classifiers.bayes.net.search.SearchAlgorithm
  Search algorithm
 
```
```
 -E weka.classifiers.bayes.net.estimate.SimpleEstimator
  Estimator algorithm
 
```
Version:

$Revision: 7836 $

Author:

Remco Bouckaert (rrb@xm.co.nz)

See Also:

Serialized Form

Field Summary
- Fields inherited from class weka.classifiers.bayes.BayesNet
  m_Distributions, m_Instances
- Fields inherited from interface weka.core.Drawable
  BayesNet, Newick, NOT_DRAWABLE, TREE

Constructor Summary

Constructors
Constructor and Description
`EditableBayesNet()` standard constructor *
`EditableBayesNet(BIFReader other)` constructor, copies Bayesian network structure from a Bayesian network encapsulated in a BIFReader
`EditableBayesNet(boolean bSetInstances)` constructor that potentially initializes instances as well
`EditableBayesNet(Instances instances)` constructor, creates empty network with nodes based on the attributes in a data set

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`addArc(int nParent, int nChild)` Add arc between two nodes Distributions are updated by duplication for every value of the parent node.
`void`	`addArc(java.lang.String sParent, FastVector nodes)` Add arc between parent node and each of the nodes in a given list.
`void`	`addArc(java.lang.String sParent, java.lang.String sChild)` Add arc between two nodes Distributions are updated by duplication for every value of the parent node.
`void`	`addNode(java.lang.String sName, int nCardinality)` Add new node to the network, initializing instances, parentsets, distributions.
`void`	`addNode(java.lang.String sName, int nCardinality, int nPosX, int nPosY)` Add node to network at a given position, initializing instances, parentsets, distributions.
`void`	`addNodeValue(int nTargetNode, java.lang.String sNewValue)` Add node value to a node.
`void`	`alignBottom(FastVector nodes)` align set of nodes with the bottom most node in the list
`void`	`alignLeft(FastVector nodes)` align set of nodes with the left most node in the list
`void`	`alignRight(FastVector nodes)` align set of nodes with the right most node in the list
`void`	`alignTop(FastVector nodes)` align set of nodes with the top most node in the list
`boolean`	`canRedo()` return whether there is something on the undo stack that can be performed
`boolean`	`canUndo()` return whether there is something on the undo stack that can be performed
`void`	`centerHorizontal(FastVector nodes)` center set of nodes half way between left and right most node in the list
`void`	`centerVertical(FastVector nodes)` center set of nodes half way between top and bottom most node in the list
`void`	`clearUndoStack()` remove all actions from the undo stack
`void`	`deleteArc(int nParent, int nChild)` Delete arc between two nodes.
`void`	`deleteArc(java.lang.String sParent, java.lang.String sChild)` Delete arc between two nodes.
`void`	`deleteNode(int nTargetNode)` Delete node from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value.
`void`	`deleteNode(java.lang.String sName)` Delete node from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value.
`void`	`deleteSelection(FastVector nodes)` Delete nodes with indexes in selection from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value.
`void`	`delNodeValue(int nTargetNode, java.lang.String sValue)` Delete node value from a node.
`FastVector`	`getChildren(int nTargetNode)` return list of children of a node
`java.lang.String`	`getContent(org.w3c.dom.Element node)` XML helper function.
`double[][]`	`getDistribution(int nTargetNode)` returns distribution of a node in matrix form with matrix representing distribution with P[i][j] = P(node = j \| parent configuration = i)
`double[][]`	`getDistribution(java.lang.String sName)` returns distribution of a node in matrix form with matrix representing distribution with P[i][j] = P(node = j \| parent configuration = i)
`int`	`getEvidence(int iNode)` get evidence state of a node.
`double[]`	`getMargin(int iNode)` return marginal distibution for a node
`int`	`getNode(java.lang.String sNodeName)` returns index of node with given name.
`int`	`getNode2(java.lang.String sNodeName)` returns index of node with given name, or -1 if no such node exists
`int`	`getPositionX(int iNode)` get x position of a node
`int`	`getPositionY(int iNode)` get y position of a node
`java.lang.String`	`getRevision()` Returns the revision string.
`java.lang.String`	`getValueName(int nTargetNode, int iValue)` returns value of a node
`java.lang.String[]`	`getValues(int nTargetNode)` returns array of values of a node
`java.lang.String[]`	`getValues(java.lang.String sName)` returns array of values of a node
`boolean`	`isChanged()` return true when current state differs from the state the network was last saved
`void`	`isSaved()` indicate the network state was saved
`java.lang.String`	`lastActionMsg()` get message representing the last action performed on the network
`void`	`layoutGraph(FastVector nPosX, FastVector nPosY)` set positions of all nodes
`static void`	`main(java.lang.String[] args)`
`void`	`paste(java.lang.String sXML)` Apply paste operation with XMLBIF fragment.
`java.lang.String`	`redo()` redo the last edit action performed on the network.
`void`	`renameNodeValue(int nTargetNode, java.lang.String sValue, java.lang.String sNewValue)` change the name of a value of a node
`void`	`setData(Instances instances)` Assuming a network structure is defined and we want to learn from data, the data set must be put if correct order first and possibly discretized/missing values filled in before proceeding to CPT learning.
`void`	`setDistribution(int nTargetNode, double[][] P)` specify distribution of a node
`void`	`setDistribution(java.lang.String sName, double[][] P)` specify distribution of a node
`void`	`setEvidence(int iNode, int iValue)` set evidence state of a node.
`void`	`setMargin(int iNode, double[] fMarginP)` set marginal distibution for a node
`void`	`setNodeName(int nTargetNode, java.lang.String sName)` change the name of a node
`void`	`setPosition(int iNode, int nX, int nY)` set position of node
`void`	`setPosition(int nNode, int nX, int nY, FastVector nodes)` Set position of node.
`void`	`spaceHorizontal(FastVector nodes)` space out set of nodes evenly between left and right most node in the list
`void`	`spaceVertical(FastVector nodes)` space out set of nodes evenly between top and bottom most node in the list
`java.lang.String`	`toXMLBIF03()` returns network in XMLBIF format
`java.lang.String`	`toXMLBIF03(FastVector nodes)` return fragment of network in XMLBIF format
`java.lang.String`	`undo()` undo the last edit action performed on the network.

Methods inherited from class weka.classifiers.bayes.BayesNet
BIFFileTipText, buildClassifier, buildStructure, countsForInstance, distributionForInstance, enumerateMeasures, estimateCPTs, estimatorTipText, getADTree, getBIFFile, getBIFHeader, getCapabilities, getCardinality, getDistributions, getEstimator, getMeasure, getName, getNodeName, getNodeValue, getNrOfNodes, getNrOfParents, getOptions, getParent, getParentCardinality, getParentSet, getParentSets, getProbability, getSearchAlgorithm, getUseADTree, globalInfo, graph, graphType, initCPTs, initStructure, listOptions, measureAICScore, measureBayesScore, measureBDeuScore, measureDivergence, measureEntropyScore, measureExtraArcs, measureMDLScore, measureMissingArcs, measureReversedArcs, partitionOptions, searchAlgorithmTipText, setBIFFile, setEstimator, setOptions, setSearchAlgorithm, setUseADTree, toString, updateClassifier, useADTreeTipText

Methods inherited from class weka.classifiers.Classifier
classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, setDebug

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

- Constructor Detail
  - EditableBayesNet
```
public EditableBayesNet()
```
    standard constructor *
  - EditableBayesNet
```
public EditableBayesNet(Instances instances)
```
    constructor, creates empty network with nodes based on the attributes in a data set
  - EditableBayesNet
```
public EditableBayesNet(BIFReader other)
```
    constructor, copies Bayesian network structure from a Bayesian network encapsulated in a BIFReader
  - EditableBayesNet
```
public EditableBayesNet(boolean bSetInstances)
```
    constructor that potentially initializes instances as well
    
    Parameters:
    
    bSetInstances - flag indicating whether to initialize instances or not
- Method Detail
  - setData
```
public void setData(Instances instances)
             throws java.lang.Exception
```
    Assuming a network structure is defined and we want to learn from data, the data set must be put if correct order first and possibly discretized/missing values filled in before proceeding to CPT learning.
    
    Parameters:
    
    instances - data set to learn from
    
    Throws:
    
    java.lang.Exception - when data sets are not compatible, e.g., a variable is missing or a variable has different nr of values.
  - getNode2
```
public int getNode2(java.lang.String sNodeName)
```
    returns index of node with given name, or -1 if no such node exists
    
    Parameters:
    
    sNodeName - name of the node to get index for
  - getNode
```
public int getNode(java.lang.String sNodeName)
            throws java.lang.Exception
```
    returns index of node with given name. Throws exception if no such node exists
    
    Parameters:
    
    sNodeName - name of the node to get index for
    
    Throws:
    
    java.lang.Exception
  - addNode
```
public void addNode(java.lang.String sName,
                    int nCardinality)
             throws java.lang.Exception
```
    Add new node to the network, initializing instances, parentsets, distributions. Used for manual manipulation of the Bayesian network.
    
    Parameters:
    
    sName - name of the node. If the name already exists, an x is appended to the name
    
    nCardinality - number of values for this node
    
    Throws:
    
    java.lang.Exception
  - addNode
```
public void addNode(java.lang.String sName,
                    int nCardinality,
                    int nPosX,
                    int nPosY)
             throws java.lang.Exception
```
    Add node to network at a given position, initializing instances, parentsets, distributions. Used for manual manipulation of the Bayesian network.
    
    Parameters:
    
    sName - name of the node. If the name already exists, an x is appended to the name
    
    nCardinality - number of values for this node
    
    nPosX - x-coordiate of the position to place this node
    
    nPosY - y-coordiate of the position to place this node
    
    Throws:
    
    java.lang.Exception
  - deleteNode
```
public void deleteNode(java.lang.String sName)
                throws java.lang.Exception
```
    Delete node from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value. Used for manual manipulation of the Bayesian network.
    
    Parameters:
    
    sName - name of the node. If the name does not exists an exception is thrown
    
    Throws:
    
    java.lang.Exception
  - deleteNode
```
public void deleteNode(int nTargetNode)
                throws java.lang.Exception
```
    Delete node from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value. Used for manual manipulation of the Bayesian network.
    
    Parameters:
    
    nTargetNode - index of the node to delete.
    
    Throws:
    
    java.lang.Exception
  - deleteSelection
```
public void deleteSelection(FastVector nodes)
```
    Delete nodes with indexes in selection from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value. Used for manual manipulation of the Bayesian network.
    
    Parameters:
    
    nodes - array of indexes of nodes to delete.
    
    Throws:
    
    java.lang.Exception
  - getContent
```
public java.lang.String getContent(org.w3c.dom.Element node)
```
    XML helper function. Returns all TEXT children of the given node in one string. Between the node values new lines are inserted.
    
    Parameters:
    
    node - the node to return the content for
    
    Returns:
    
    the content of the node
  - paste
```
public void paste(java.lang.String sXML)
           throws java.lang.Exception
```
    Apply paste operation with XMLBIF fragment. This adds nodes in the XMLBIF fragment to the network, together with its parents. First, paste in test mode to verify no problems occur, then execute paste operation. If a problem occurs (e.g. parent does not exist) then a exception is thrown.
    
    Parameters:
    
    sXML - XMLBIF fragment to paste into the network
    
    Throws:
    
    java.lang.Exception
  - addArc
```
public void addArc(java.lang.String sParent,
                   java.lang.String sChild)
            throws java.lang.Exception
```
    Add arc between two nodes Distributions are updated by duplication for every value of the parent node.
    
    Parameters:
    
    sParent - name of the parent node
    
    sChild - name of the child node
    
    Throws:
    
    java.lang.Exception - if parent or child cannot be found in network
  - addArc
```
public void addArc(int nParent,
                   int nChild)
            throws java.lang.Exception
```
    Add arc between two nodes Distributions are updated by duplication for every value of the parent node.
    
    Parameters:
    
    nParent - index of the parent node
    
    nChild - index of the child node
    
    Throws:
    
    java.lang.Exception
  - addArc
```
public void addArc(java.lang.String sParent,
                   FastVector nodes)
            throws java.lang.Exception
```
    Add arc between parent node and each of the nodes in a given list. Distributions are updated as above.
    
    Parameters:
    
    sParent - name of the parent node
    
    nodes - array of indexes of child nodes
    
    Throws:
    
    java.lang.Exception
  - deleteArc
```
public void deleteArc(java.lang.String sParent,
                      java.lang.String sChild)
               throws java.lang.Exception
```
    Delete arc between two nodes. Distributions are updated by condensing for the parent node taking its first value.
    
    Parameters:
    
    sParent - name of the parent node
    
    sChild - name of the child node
    
    Throws:
    
    java.lang.Exception - if parent or child cannot be found in network
  - deleteArc
```
public void deleteArc(int nParent,
                      int nChild)
               throws java.lang.Exception
```
    Delete arc between two nodes. Distributions are updated by condensing for the parent node taking its first value.
    
    Parameters:
    
    nParent - index of the parent node
    
    nChild - index of the child node
    
    Throws:
    
    java.lang.Exception
  - setDistribution
```
public void setDistribution(java.lang.String sName,
                            double[][] P)
                     throws java.lang.Exception
```
    specify distribution of a node
    
    Parameters:
    
    sName - name of the node to specify distribution for
    
    P - matrix representing distribution with P[i][j] = P(node = j | parent configuration = i)
    
    Throws:
    
    java.lang.Exception - if parent or child cannot be found in network
  - setDistribution
```
public void setDistribution(int nTargetNode,
                            double[][] P)
                     throws java.lang.Exception
```
    specify distribution of a node
    
    Parameters:
    
    nTargetNode - index of the node to specify distribution for
    
    P - matrix representing distribution with P[i][j] = P(node = j | parent configuration = i)
    
    Throws:
    
    java.lang.Exception - if parent or child cannot be found in network
  - getDistribution
```
public double[][] getDistribution(java.lang.String sName)
```
    returns distribution of a node in matrix form with matrix representing distribution with P[i][j] = P(node = j | parent configuration = i)
    
    Parameters:
    
    sName - name of the node to get distribution from
  - getDistribution
```
public double[][] getDistribution(int nTargetNode)
```
    returns distribution of a node in matrix form with matrix representing distribution with P[i][j] = P(node = j | parent configuration = i)
    
    Parameters:
    
    nTargetNode - index of the node to get distribution from
  - getValues
```
public java.lang.String[] getValues(java.lang.String sName)
```
    returns array of values of a node
    
    Parameters:
    
    sName - name of the node to get values from
  - getValues
```
public java.lang.String[] getValues(int nTargetNode)
```
    returns array of values of a node
    
    Parameters:
    
    nTargetNode - index of the node to get values from
  - getValueName
```
public java.lang.String getValueName(int nTargetNode,
                                     int iValue)
```
    returns value of a node
    
    Parameters:
    
    nTargetNode - index of the node to get values from
    
    iValue - index of the value
  - setNodeName
```
public void setNodeName(int nTargetNode,
                        java.lang.String sName)
```
    change the name of a node
    
    Parameters:
    
    nTargetNode - index of the node to set name for
    
    sName - new name to assign
  - renameNodeValue
```
public void renameNodeValue(int nTargetNode,
                            java.lang.String sValue,
                            java.lang.String sNewValue)
```
    change the name of a value of a node
    
    Parameters:
    
    nTargetNode - index of the node to set name for
    
    sValue - current name of the value
    
    sNewValue - new name of the value
  - addNodeValue
```
public void addNodeValue(int nTargetNode,
                         java.lang.String sNewValue)
```
    Add node value to a node. Distributions for the node assign zero probability to the new value. Child nodes duplicate CPT conditioned on the new value.
    
    Parameters:
    
    nTargetNode - index of the node to add value for
    
    sNewValue - name of the value
  - delNodeValue
```
public void delNodeValue(int nTargetNode,
                         java.lang.String sValue)
                  throws java.lang.Exception
```
    Delete node value from a node. Distributions for the node are scaled up proportional to existing distribution (or made uniform if zero probability is assigned to remainder of values). .* Child nodes delete CPTs conditioned on the new value.
    
    Parameters:
    
    nTargetNode - index of the node to delete value from
    
    sValue - name of the value to delete
    
    Throws:
    
    java.lang.Exception
  - setPosition
```
public void setPosition(int iNode,
                        int nX,
                        int nY)
```
    set position of node
    
    Parameters:
    
    iNode - index of node to set position for
    
    nX - x position of new position
    
    nY - y position of new position
  - setPosition
```
public void setPosition(int nNode,
                        int nX,
                        int nY,
                        FastVector nodes)
```
    Set position of node. Move set of nodes with the same displacement as a specified node.
    
    Parameters:
    
    iNode - index of node to set position for
    
    nX - x position of new position
    
    nY - y position of new position
    
    nodes - array of indexes of nodes to move
  - layoutGraph
```
public void layoutGraph(FastVector nPosX,
                        FastVector nPosY)
```
    set positions of all nodes
    
    Parameters:
    
    nPosX - new x positions for all nodes
    
    nPosY - new y positions for all nodes
  - getPositionX
```
public int getPositionX(int iNode)
```
    get x position of a node
    
    Parameters:
    
    iNode - index of node of interest
  - getPositionY
```
public int getPositionY(int iNode)
```
    get y position of a node
    
    Parameters:
    
    iNode - index of node of interest
  - alignLeft
```
public void alignLeft(FastVector nodes)
```
    align set of nodes with the left most node in the list
    
    Parameters:
    
    nodes - list of indexes of nodes to align
  - alignRight
```
public void alignRight(FastVector nodes)
```
    align set of nodes with the right most node in the list
    
    Parameters:
    
    nodes - list of indexes of nodes to align
  - alignTop
```
public void alignTop(FastVector nodes)
```
    align set of nodes with the top most node in the list
    
    Parameters:
    
    nodes - list of indexes of nodes to align
  - alignBottom
```
public void alignBottom(FastVector nodes)
```
    align set of nodes with the bottom most node in the list
    
    Parameters:
    
    nodes - list of indexes of nodes to align
  - centerHorizontal
```
public void centerHorizontal(FastVector nodes)
```
    center set of nodes half way between left and right most node in the list
    
    Parameters:
    
    nodes - list of indexes of nodes to center
  - centerVertical
```
public void centerVertical(FastVector nodes)
```
    center set of nodes half way between top and bottom most node in the list
    
    Parameters:
    
    nodes - list of indexes of nodes to center
  - spaceHorizontal
```
public void spaceHorizontal(FastVector nodes)
```
    space out set of nodes evenly between left and right most node in the list
    
    Parameters:
    
    nodes - list of indexes of nodes to space out
  - spaceVertical
```
public void spaceVertical(FastVector nodes)
```
    space out set of nodes evenly between top and bottom most node in the list
    
    Parameters:
    
    nodes - list of indexes of nodes to space out
  - getMargin
```
public double[] getMargin(int iNode)
```
    return marginal distibution for a node
    
    Parameters:
    
    iNode - index of node of interest
  - setMargin
```
public void setMargin(int iNode,
                      double[] fMarginP)
```
    set marginal distibution for a node
    
    Parameters:
    
    iNode - index of node to set marginal distribution for
    
    fMarginP - marginal distribution
  - getEvidence
```
public int getEvidence(int iNode)
```
    get evidence state of a node. -1 represents no evidence set, otherwise the index of a value of the node
    
    Parameters:
    
    iNode - index of node of interest
  - setEvidence
```
public void setEvidence(int iNode,
                        int iValue)
```
    set evidence state of a node. -1 represents no evidence set, otherwise the index of a value of the node
    
    Parameters:
    
    iNode - index of node of interest
    
    iValue - evidence value to set
  - getChildren
```
public FastVector getChildren(int nTargetNode)
```
    return list of children of a node
    
    Parameters:
    
    iNode - index of node of interest
  - toXMLBIF03
```
public java.lang.String toXMLBIF03()
```
    returns network in XMLBIF format
    
    Overrides:
    
    toXMLBIF03 in class BayesNet
    
    Returns:
    
    an XML BIF 0.3 description of the classifier as a string.
  - toXMLBIF03
```
public java.lang.String toXMLBIF03(FastVector nodes)
```
    return fragment of network in XMLBIF format
    
    Parameters:
    
    nodes - array of indexes of nodes that should be in the fragment
  - canUndo
```
public boolean canUndo()
```
    return whether there is something on the undo stack that can be performed
  - canRedo
```
public boolean canRedo()
```
    return whether there is something on the undo stack that can be performed
  - isChanged
```
public boolean isChanged()
```
    return true when current state differs from the state the network was last saved
  - isSaved
```
public void isSaved()
```
    indicate the network state was saved
  - lastActionMsg
```
public java.lang.String lastActionMsg()
```
    get message representing the last action performed on the network
  - undo
```
public java.lang.String undo()
```
    undo the last edit action performed on the network. returns message representing the action performed.
  - redo
```
public java.lang.String redo()
```
    redo the last edit action performed on the network. returns message representing the action performed.
  - clearUndoStack
```
public void clearUndoStack()
```
    remove all actions from the undo stack
  - getRevision
```
public java.lang.String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class BayesNet
    
    Returns:
    
    the revision
  - main
```
public static void main(java.lang.String[] args)
```
    Parameters:
    
    args -

Class EditableBayesNet

Field Summary

Fields inherited from class weka.classifiers.bayes.BayesNet

Fields inherited from interface weka.core.Drawable

Constructor Summary

Method Summary

Methods inherited from class weka.classifiers.bayes.BayesNet

Methods inherited from class weka.classifiers.Classifier

Methods inherited from class java.lang.Object

Constructor Detail

EditableBayesNet

EditableBayesNet

EditableBayesNet

EditableBayesNet

Method Detail

setData

getNode2

getNode

addNode

addNode

deleteNode

deleteNode

deleteSelection

getContent

paste

addArc

addArc

addArc

deleteArc

deleteArc

setDistribution

setDistribution

getDistribution

getDistribution

getValues

getValues

getValueName

setNodeName

renameNodeValue

addNodeValue

delNodeValue

setPosition

setPosition

layoutGraph

getPositionX

getPositionY

alignLeft

alignRight

alignTop

alignBottom

centerHorizontal

centerVertical

spaceHorizontal

spaceVertical

getMargin

setMargin

getEvidence

setEvidence

getChildren

toXMLBIF03

toXMLBIF03

canUndo

canRedo

isChanged

isSaved

lastActionMsg

undo

redo

clearUndoStack

getRevision

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