PS (meka 1.9.1 API)

java.lang.Object
- weka.classifiers.AbstractClassifier
- - weka.classifiers.SingleClassifierEnhancer
  - - meka.classifiers.multilabel.ProblemTransformationMethod
    - - meka.classifiers.multilabel.LC
      - meka.classifiers.multilabel.PS

All Implemented Interfaces:

Serializable, Cloneable, MultiLabelClassifier, MultiLabelDrawable, weka.classifiers.Classifier, weka.core.BatchPredictor, weka.core.CapabilitiesHandler, weka.core.CapabilitiesIgnorer, weka.core.CommandlineRunnable, weka.core.OptionHandler, weka.core.Randomizable, weka.core.RevisionHandler, weka.core.TechnicalInformationHandler

Direct Known Subclasses:

NSR, PSt, PSUpdateable, RAkELd
```
public class PS
extends LC
implements weka.core.Randomizable, weka.core.TechnicalInformationHandler
```
PS.java - The Pruned Sets Method. Removes examples with P-infrequent labelsets from the training data, then subsamples these labelsets N time to produce N new examples with P-frequent labelsets. Then train a standard LC classifier. The idea is to reduce the number of unique class values that would otherwise need to be learned by LC. Best used in an Ensemble (e.g., EnsembleML).
This class was rewritten and extended to be faster, use sparse LabelSets, and better OOP. There may be minor variation in results (probably on account of internal randomness, different set orderings, etc) but this should not be statistically significant.
See: Jesse Read, Bernhard Pfahringer, Geoff Holmes. Multi-label Classification using Ensembles of Pruned Sets. Proc. of IEEE International Conference on Data Mining (ICDM 2008), Pisa, Italy, 2008

Version:

April 2014

Author:

Jesse Read

See Also:

LC, Serialized Form

Field Summary

Fields
Modifier and Type Field and Description

protected int m_N

protected int m_P

protected int m_S
- Fields inherited from class meka.classifiers.multilabel.ProblemTransformationMethod
  m_InstancesTemplate
- Fields inherited from class weka.classifiers.SingleClassifierEnhancer
  m_Classifier
- Fields inherited from class weka.classifiers.AbstractClassifier
  BATCH_SIZE_DEFAULT, m_BatchSize, m_Debug, m_DoNotCheckCapabilities, m_numDecimalPlaces, NUM_DECIMAL_PLACES_DEFAULT
- Fields inherited from interface meka.core.MultiLabelDrawable
  BayesNet, Newick, NOT_DRAWABLE, TREE

Fields
Modifier and Type	Field and Description
`protected int`	`m_N`
`protected int`	`m_P`
`protected int`	`m_S`

Constructor Summary

Constructors
Constructor and Description

PS()

Constructors
Constructor and Description
`PS()`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`buildClassifier(weka.core.Instances D)`
`int`	`getN()` GetN - Get the subsampling value N.
`String[]`	`getOptions()`
`int`	`getP()` GetP - Get the pruning value P.
`String`	`getRevision()`
`int`	`getSeed()`
`weka.core.TechnicalInformation`	`getTechnicalInformation()`
`String`	`globalInfo()` Description to display in the GUI.
`Enumeration`	`listOptions()`
`static void`	`main(String[] args)`
`String`	`nTipText()`
`String`	`pTipText()`
`String`	`seedTipText()`
`void`	`setN(int n)` SetN - Sets the subsampling value N, the (maximum) number of frequent labelsets to subsample from the infrequent labelsets.
`void`	`setOptions(String[] options)`
`void`	`setP(int p)` SetP - Sets the pruning value P, defining an infrequent labelset as one which occurs less than P times in the data (P = 0 defaults to LC).
`void`	`setSeed(int s)` SetSeed - Use random P and N values (in this case P and N arguments determine a range of values to select from randomly, e.g., -P 1-5 selects P randomly in {1,2,3,4,5}.

Methods inherited from class meka.classifiers.multilabel.LC
distributionForInstance, graph, graphType, toString

Methods inherited from class meka.classifiers.multilabel.ProblemTransformationMethod
defaultClassifierString, evaluation, getCapabilities, getModel, getTemplate, makeCopies, runClassifier, testCapabilities

Methods inherited from class weka.classifiers.SingleClassifierEnhancer
classifierTipText, defaultClassifierOptions, getClassifier, getClassifierSpec, postExecution, preExecution, setClassifier

Methods inherited from class weka.classifiers.AbstractClassifier
batchSizeTipText, classifyInstance, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces

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

Methods inherited from interface meka.classifiers.multilabel.MultiLabelClassifier
debugTipText, getDebug, setDebug

Methods inherited from interface weka.classifiers.Classifier
classifyInstance

- Field Detail
  - m_P
```
protected int m_P
```
  - m_N
```
protected int m_N
```
  - m_S
```
protected int m_S
```
- Constructor Detail
  - PS
```
public PS()
```
- Method Detail
  - globalInfo
```
public String globalInfo()
```
    Description to display in the GUI.
    
    Overrides:
    
    globalInfo in class LC
    
    Returns:
    
    the description
  - getTechnicalInformation
```
public weka.core.TechnicalInformation getTechnicalInformation()
```
    Specified by:
    
    getTechnicalInformation in interface weka.core.TechnicalInformationHandler
  - getP
```
public int getP()
```
    GetP - Get the pruning value P.
  - setP
```
public void setP(int p)
```
    SetP - Sets the pruning value P, defining an infrequent labelset as one which occurs less than P times in the data (P = 0 defaults to LC).
  - pTipText
```
public String pTipText()
```
  - getN
```
public int getN()
```
    GetN - Get the subsampling value N.
  - setN
```
public void setN(int n)
```
    SetN - Sets the subsampling value N, the (maximum) number of frequent labelsets to subsample from the infrequent labelsets.
  - nTipText
```
public String nTipText()
```
  - setSeed
```
public void setSeed(int s)
```
    SetSeed - Use random P and N values (in this case P and N arguments determine a range of values to select from randomly, e.g., -P 1-5 selects P randomly in {1,2,3,4,5}.
    
    Specified by:
    
    setSeed in interface weka.core.Randomizable
  - getSeed
```
public int getSeed()
```
    Specified by:
    
    getSeed in interface weka.core.Randomizable
  - seedTipText
```
public String seedTipText()
```
  - listOptions
```
public Enumeration listOptions()
```
    Specified by:
    
    listOptions in interface weka.core.OptionHandler
    
    Overrides:
    
    listOptions in class weka.classifiers.SingleClassifierEnhancer
  - setOptions
```
public void setOptions(String[] options)
                throws Exception
```
    Specified by:
    
    setOptions in interface weka.core.OptionHandler
    
    Overrides:
    
    setOptions in class weka.classifiers.SingleClassifierEnhancer
    
    Throws:
    
    Exception
  - getOptions
```
public String[] getOptions()
```
    Specified by:
    
    getOptions in interface weka.core.OptionHandler
    
    Overrides:
    
    getOptions in class weka.classifiers.SingleClassifierEnhancer
  - buildClassifier
```
public void buildClassifier(weka.core.Instances D)
                     throws Exception
```
    Specified by:
    
    buildClassifier in interface weka.classifiers.Classifier
    
    Overrides:
    
    buildClassifier in class LC
    
    Throws:
    
    Exception
  - getRevision
```
public String getRevision()
```
    Specified by:
    
    getRevision in interface weka.core.RevisionHandler
    
    Overrides:
    
    getRevision in class LC
  - main
```
public static void main(String[] args)
```

Class PS

Field Summary

Fields inherited from class meka.classifiers.multilabel.ProblemTransformationMethod

Fields inherited from class weka.classifiers.SingleClassifierEnhancer

Fields inherited from class weka.classifiers.AbstractClassifier

Fields inherited from interface meka.core.MultiLabelDrawable

Constructor Summary

Method Summary

Methods inherited from class meka.classifiers.multilabel.LC

Methods inherited from class meka.classifiers.multilabel.ProblemTransformationMethod

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

Methods inherited from class weka.classifiers.AbstractClassifier

Methods inherited from class java.lang.Object

Methods inherited from interface meka.classifiers.multilabel.MultiLabelClassifier

Methods inherited from interface weka.classifiers.Classifier

Field Detail

m_P

m_N

m_S

Constructor Detail

PS

Method Detail

globalInfo

getTechnicalInformation

getP

setP

pTipText

getN

setN

nTipText

setSeed

getSeed

seedTipText

listOptions

setOptions

getOptions

buildClassifier

getRevision

main