sIB

java.lang.Object
- weka.clusterers.AbstractClusterer
- - weka.clusterers.RandomizableClusterer
  - - weka.clusterers.sIB

All Implemented Interfaces:: java.io.Serializable, java.lang.Cloneable, Clusterer, CapabilitiesHandler, OptionHandler, Randomizable, RevisionHandler, TechnicalInformationHandler

public class sIB
extends RandomizableClusterer
implements TechnicalInformationHandler

Cluster data using the sequential information bottleneck algorithm.

Note: only hard clustering scheme is supported. sIB assign for each instance the cluster that have the minimum cost/distance to the instance. The trade-off beta is set to infinite so 1/beta is zero.

For more information, see:

Noam Slonim, Nir Friedman, Naftali Tishby: Unsupervised document classification using sequential information maximization. In: Proceedings of the 25th International ACM SIGIR Conference on Research and Development in Information Retrieval, 129-136, 2002.

BibTeX:

 @inproceedings{Slonim2002,
    author = {Noam Slonim and Nir Friedman and Naftali Tishby},
    booktitle = {Proceedings of the 25th International ACM SIGIR Conference on Research and Development in Information Retrieval},
    pages = {129-136},
    title = {Unsupervised document classification using sequential information maximization},
    year = {2002}
 }

Valid options are:

 -I <num>
  maximum number of iterations
  (default 100).

 -M <num>
  minimum number of changes in a single iteration
  (default 0).

 -N <num>
  number of clusters.
  (default 2).

 -R <num>
  number of restarts.
  (default 5).

 -U
  set not to normalize the data
  (default true).

 -V
  set to output debug info
  (default false).

 -S <num>
  Random number seed.
  (default 1)

Version:: $Revision: 5538 $
Author:: Noam Slonim, Anna Huang
See Also:: Serialized Form

Constructor Summary

Constructors
Constructor and Description

sIB()

Constructors
Constructor and Description
`sIB()`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`buildClusterer(Instances data)` Generates a clusterer.
`int`	`clusterInstance(Instance instance)` Cluster a given instance, this is the method defined in Clusterer interface do nothing but just return the cluster assigned to it
`java.lang.String`	`debugTipText()` Returns the tip text for this property
`Capabilities`	`getCapabilities()` Returns default capabilities of the clusterer.
`boolean`	`getDebug()` Get debug mode
`int`	`getMaxIterations()` Get the max number of iterations
`int`	`getMinChange()` get the minimum number of changes
`boolean`	`getNotUnifyNorm()` Get whether to normalize instances to unify prior probability before building the clusterer
`int`	`getNumClusters()` Get the number of clusters
`int`	`getNumRestarts()` Get the number of restarts
`java.lang.String[]`	`getOptions()` Gets the current settings.
`java.lang.String`	`getRevision()` Returns the revision string.
`TechnicalInformation`	`getTechnicalInformation()` Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
`java.lang.String`	`globalInfo()` Returns a string describing this clusterer
`java.util.Enumeration`	`listOptions()` Returns an enumeration describing the available options.
`static void`	`main(java.lang.String[] argv)`
`java.lang.String`	`maxIterationsTipText()` Returns the tip text for this property.
`java.lang.String`	`minChangeTipText()` Returns the tip text for this property.
`java.lang.String`	`notUnifyNormTipText()` Returns the tip text for this property.
`int`	`numberOfClusters()` Get the number of clusters
`java.lang.String`	`numClustersTipText()` Returns the tip text for this property.
`java.lang.String`	`numRestartsTipText()` Returns the tip text for this property.
`void`	`setDebug(boolean v)` Set debug mode - verbose output
`void`	`setMaxIterations(int i)` Set the max number of iterations
`void`	`setMinChange(int m)` set the minimum number of changes
`void`	`setNotUnifyNorm(boolean b)` Set whether to normalize instances to unify prior probability before building the clusterer
`void`	`setNumClusters(int n)` Set the number of clusters
`void`	`setNumRestarts(int i)` Set the number of restarts
`void`	`setOptions(java.lang.String[] options)` Parses a given list of options.
`java.lang.String`	`toString()`

Methods inherited from class weka.clusterers.RandomizableClusterer
getSeed, seedTipText, setSeed

Methods inherited from class weka.clusterers.AbstractClusterer
distributionForInstance, forName, makeCopies, makeCopy

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

- Constructor Detail
  - sIB
```
public sIB()
```
- Method Detail
  - buildClusterer
```
public void buildClusterer(Instances data)
                    throws java.lang.Exception
```
    Generates a clusterer.
    
    Specified by:
    
    buildClusterer in interface Clusterer
    
    Specified by:
    
    buildClusterer in class AbstractClusterer
    
    Parameters:
    
    data - the training instances
    
    Throws:
    
    java.lang.Exception - if something goes wrong
  - clusterInstance
```
public int clusterInstance(Instance instance)
                    throws java.lang.Exception
```
    Cluster a given instance, this is the method defined in Clusterer interface do nothing but just return the cluster assigned to it
    
    Specified by:
    
    clusterInstance in interface Clusterer
    
    Overrides:
    
    clusterInstance in class AbstractClusterer
    
    Parameters:
    
    instance - the instance to be assigned to a cluster
    
    Returns:
    
    the number of the assigned cluster as an integer
    
    Throws:
    
    java.lang.Exception - if instance could not be clustered successfully
  - setOptions
```
public void setOptions(java.lang.String[] options)
                throws java.lang.Exception
```
    Parses a given list of options.
    Valid options are:
```
 -I <num>
  maximum number of iterations
  (default 100).
```
```
 -M <num>
  minimum number of changes in a single iteration
  (default 0).
```
```
 -N <num>
  number of clusters.
  (default 2).
```
```
 -R <num>
  number of restarts.
  (default 5).
```
```
 -U
  set not to normalize the data
  (default true).
```
```
 -V
  set to output debug info
  (default false).
```
```
 -S <num>
  Random number seed.
  (default 1)
```
    Specified by:
    
    setOptions in interface OptionHandler
    
    Overrides:
    
    setOptions in class RandomizableClusterer
    
    Parameters:
    
    options - the list of options as an array of strings
    
    Throws:
    
    java.lang.Exception - if an option is not supported
  - listOptions
```
public java.util.Enumeration listOptions()
```
    Returns an enumeration describing the available options.
    
    Specified by:
    
    listOptions in interface OptionHandler
    
    Overrides:
    
    listOptions in class RandomizableClusterer
    
    Returns:
    
    an enumeration of all the available options.
  - getOptions
```
public java.lang.String[] getOptions()
```
    Gets the current settings.
    
    Specified by:
    
    getOptions in interface OptionHandler
    
    Overrides:
    
    getOptions in class RandomizableClusterer
    
    Returns:
    
    an array of strings suitable for passing to setOptions()
  - debugTipText
```
public java.lang.String debugTipText()
```
    Returns the tip text for this property
    
    Returns:
    
    tip text for this property suitable for displaying in the explorer/experimenter gui
  - setDebug
```
public void setDebug(boolean v)
```
    Set debug mode - verbose output
    
    Parameters:
    
    v - true for verbose output
  - getDebug
```
public boolean getDebug()
```
    Get debug mode
    
    Returns:
    
    true if debug mode is set
  - maxIterationsTipText
```
public java.lang.String maxIterationsTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property
  - setMaxIterations
```
public void setMaxIterations(int i)
```
    Set the max number of iterations
    
    Parameters:
    
    i - max number of iterations
  - getMaxIterations
```
public int getMaxIterations()
```
    Get the max number of iterations
    
    Returns:
    
    max number of iterations
  - minChangeTipText
```
public java.lang.String minChangeTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property
  - setMinChange
```
public void setMinChange(int m)
```
    set the minimum number of changes
    
    Parameters:
    
    m - the minimum number of changes
  - getMinChange
```
public int getMinChange()
```
    get the minimum number of changes
    
    Returns:
    
    the minimum number of changes
  - numClustersTipText
```
public java.lang.String numClustersTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property
  - setNumClusters
```
public void setNumClusters(int n)
```
    Set the number of clusters
    
    Parameters:
    
    n - number of clusters
  - getNumClusters
```
public int getNumClusters()
```
    Get the number of clusters
    
    Returns:
    
    the number of clusters
  - numberOfClusters
```
public int numberOfClusters()
```
    Get the number of clusters
    
    Specified by:
    
    numberOfClusters in interface Clusterer
    
    Specified by:
    
    numberOfClusters in class AbstractClusterer
    
    Returns:
    
    the number of clusters
  - numRestartsTipText
```
public java.lang.String numRestartsTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property
  - setNumRestarts
```
public void setNumRestarts(int i)
```
    Set the number of restarts
    
    Parameters:
    
    i - number of restarts
  - getNumRestarts
```
public int getNumRestarts()
```
    Get the number of restarts
    
    Returns:
    
    number of restarts
  - notUnifyNormTipText
```
public java.lang.String notUnifyNormTipText()
```
    Returns the tip text for this property.
    
    Returns:
    
    tip text for this property
  - setNotUnifyNorm
```
public void setNotUnifyNorm(boolean b)
```
    Set whether to normalize instances to unify prior probability before building the clusterer
    
    Parameters:
    
    b - true to normalize, otherwise false
  - getNotUnifyNorm
```
public boolean getNotUnifyNorm()
```
    Get whether to normalize instances to unify prior probability before building the clusterer
    
    Returns:
    
    true if set to normalize, false otherwise
  - globalInfo
```
public java.lang.String globalInfo()
```
    Returns a string describing this clusterer
    
    Returns:
    
    a description of the clusterer suitable for displaying in the explorer/experimenter gui
  - getTechnicalInformation
```
public TechnicalInformation getTechnicalInformation()
```
    Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
    
    Specified by:
    
    getTechnicalInformation in interface TechnicalInformationHandler
    
    Returns:
    
    the technical information about this class
  - getCapabilities
```
public Capabilities getCapabilities()
```
    Returns default capabilities of the clusterer.
    
    Specified by:
    
    getCapabilities in interface Clusterer
    
    Specified by:
    
    getCapabilities in interface CapabilitiesHandler
    
    Overrides:
    
    getCapabilities in class AbstractClusterer
    
    Returns:
    
    the capabilities of this clusterer
    
    See Also:
    
    Capabilities
  - toString
```
public java.lang.String toString()
```
    Overrides:
    
    toString in class java.lang.Object
  - getRevision
```
public java.lang.String getRevision()
```
    Returns the revision string.
    
    Specified by:
    
    getRevision in interface RevisionHandler
    
    Overrides:
    
    getRevision in class AbstractClusterer
    
    Returns:
    
    the revision
  - main
```
public static void main(java.lang.String[] argv)
```

Class sIB

Constructor Summary

Method Summary

Methods inherited from class weka.clusterers.RandomizableClusterer

Methods inherited from class weka.clusterers.AbstractClusterer

Methods inherited from class java.lang.Object

Constructor Detail

sIB

Method Detail

buildClusterer

clusterInstance

setOptions

listOptions

getOptions

debugTipText

setDebug

getDebug

maxIterationsTipText

setMaxIterations

getMaxIterations

minChangeTipText

setMinChange

getMinChange

numClustersTipText

setNumClusters

getNumClusters

numberOfClusters

numRestartsTipText

setNumRestarts

getNumRestarts

notUnifyNormTipText

setNotUnifyNorm

getNotUnifyNorm

globalInfo

getTechnicalInformation

getCapabilities

toString

getRevision

main