Liblinear (MaltParser 1.4.1)
Date: 2010-07-15

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## org.maltparser.ml.liblinear
Class Liblinear

    java.lang.Object
      org.maltparser.ml.liblinear.Liblinear

All Implemented Interfaces:
  LearningMethod

    public class Liblinear

extends Object
implements LearningMethod

Nested Class Summary
`static class` | `Liblinear.Verbostity`

Field Summary
`protected boolean` | `excludeNullValues`
`protected int` | `learnerMode`
`static String` | `LIBLINEAR_VERSION`
`protected String` | `name`
`protected int` | `numberOfInstances`
`protected InstanceModel` | `owner`
`protected String` | `pathExternalLiblinearTrain`
`protected boolean` | `saveInstanceFiles`

Fields inherited from interface org.maltparser.ml.LearningMethod
`BATCH, CLASSIFY`

Constructor Summary
`Liblinear(InstanceModel owner, Integer learnerMode)` Constructs a Liblinear learner.

Method Summary
`void` | `addInstance(SingleDecision decision, FeatureVector featureVector)`
`protected void` | `closeInstanceWriter()`
`Map<Integer,Integer>` | `createFeatureIdToCountMap(ArrayList<Integer> divideFeatureIndexVector)`
`double` | `crossValidate(FeatureVector featureVector, int nrOfSplits)` This method does a cross validation of the training instances added and return the average score over the nrOfSplit divisions.
`void` | `decreaseNumberOfInstances()`
`void` | `divideByFeatureSet(Set<Integer> featureIdsToCreateSeparateBranchesForSet, ArrayList<Integer> divideFeatureIndexVector, String otherId)`
`protected void` | `finalize()`
`void` | `finalizeSentence(DependencyStructure dependencyGraph)`
`double` | `getBias()`
`protected JarEntry` | `getConfigFileEntry(String suffix)`
`DependencyParserConfig` | `getConfiguration()` Returns the current configuration
`protected File` | `getFile(String suffix)`
`protected InputStreamReader` | `getInstanceInputStreamReader(String suffix)`
`protected InputStreamReader` | `getInstanceInputStreamReaderFromConfigFile(String suffix)`
`protected OutputStreamWriter` | `getInstanceOutputStreamWriter(String suffix)`
`BufferedWriter` | `getInstanceWriter()`
`int` | `getLearnerMode()`
`String` | `getLearningMethodName()`
`String` | `getLibLinearOptions()`
`liblinear.Parameter` | `getLiblinearParameters()`
`String[]` | `getLibLinearParamStringArray()`
`int` | `getNumberOfInstances()`
`InstanceModel` | `getOwner()`
`String` | `getParamString()` Returns the parameter string for used for configure Liblinear
`void` | `increaseNumberOfInstances()`
`void` | `initLiblinearOptions()`
`protected void` | `initSpecialParameters()`
`void` | `liblinear_predict_with_kbestlist(liblinear.Model model, liblinear.FeatureNode[] x, KBestList kBestList)`
`static void` | `maltSVMFormat2OriginalSVMFormat(InputStreamReader isr, OutputStreamWriter osw, int[] cardinalities)` Converts the instance file (Malt's own SVM format) into the Liblinear (SVMLight) format.
`void` | `moveAllInstances(LearningMethod method, FeatureFunction divideFeature, ArrayList<Integer> divideFeatureIndexVector)`
`void` | `noMoreInstances()`
`void` | `parseParameters(String paramstring)`
`boolean` | `predict(FeatureVector featureVector, SingleDecision decision)`
`liblinear.Problem` | `readLibLinearProblem(InputStreamReader isr, int[] cardinalities)` Reads an instance file into a svm_problem object according to the Malt-SVM format, which is column fixed format (tab-separated).
`void` | `setLearnerMode(int learnerMode)`
`protected void` | `setLearningMethodName(String name)`
`protected void` | `setNumberOfInstances(int numberOfInstances)`
`protected void` | `setOwner(InstanceModel owner)`
`void` | `terminate()`
`String` | `toString()`
`void` | `train(FeatureVector featureVector)`

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

Field Detail

### LIBLINEAR_VERSION

    public static final String LIBLINEAR_VERSION

See Also:
  Constant Field Values

### owner

    protected InstanceModel owner

### learnerMode

    protected int learnerMode

### name

    protected String name

### numberOfInstances

    protected int numberOfInstances

### saveInstanceFiles

    protected boolean saveInstanceFiles

### excludeNullValues

    protected boolean excludeNullValues

### pathExternalLiblinearTrain

    protected String pathExternalLiblinearTrain

Constructor Detail

### Liblinear

    public Liblinear(InstanceModel owner,
                     Integer learnerMode)
              throws MaltChainedException

  Constructs a Liblinear learner.

  Parameters:
    `owner` - the guide model owner
    `learnerMode` - the mode of the learner TRAIN or CLASSIFY
  Throws:
    `MaltChainedException`

Method Detail

### addInstance

    public void addInstance(SingleDecision decision,
                            FeatureVector featureVector)
                     throws MaltChainedException

  Specified by:
    `addInstance` in interface `LearningMethod`
  Throws:
    `MaltChainedException`

### finalizeSentence

    public void finalizeSentence(DependencyStructure dependencyGraph)
                          throws MaltChainedException

  Specified by:
    `finalizeSentence` in interface `LearningMethod`
  Throws:
    `MaltChainedException`

### noMoreInstances

    public void noMoreInstances()
                         throws MaltChainedException

  Specified by:
    `noMoreInstances` in interface `LearningMethod`
  Throws:
    `MaltChainedException`

### train

    public void train(FeatureVector featureVector)
               throws MaltChainedException

  Specified by:
    `train` in interface `LearningMethod`
  Throws:
    `MaltChainedException`

### crossValidate

    public double crossValidate(FeatureVector featureVector,
                                int nrOfSplits)
                         throws MaltChainedException

  Description copied from interface: `LearningMethod`
  This method does a cross validation of the training instances added and return the average score over the nrOfSplit divisions. This method is used by the decision tree model when deciding which parts of the tree that shall be pruned.

  Specified by:
    `crossValidate` in interface `LearningMethod`
  Returns:
    a double
  Throws:
    `MaltChainedException`

### moveAllInstances

    public void moveAllInstances(LearningMethod method,
                                 FeatureFunction divideFeature,
                                 ArrayList<Integer> divideFeatureIndexVector)
                          throws MaltChainedException

  Specified by:
    `moveAllInstances` in interface `LearningMethod`
  Throws:
    `MaltChainedException`

### predict

    public boolean predict(FeatureVector featureVector,
                           SingleDecision decision)
                    throws MaltChainedException

  Specified by:
    `predict` in interface `LearningMethod`
  Throws:
    `MaltChainedException`

### terminate

    public void terminate()
                   throws MaltChainedException

  Specified by:
    `terminate` in interface `LearningMethod`
  Throws:
    `MaltChainedException`

### getInstanceWriter

    public BufferedWriter getInstanceWriter()

  Specified by:
    `getInstanceWriter` in interface `LearningMethod`

### closeInstanceWriter

    protected void closeInstanceWriter()
                                throws MaltChainedException

  Throws:
    `MaltChainedException`

### getParamString

    public String getParamString()

  Returns the parameter string for used for configure Liblinear

  Returns:
    the parameter string for used for configure Liblinear

### getOwner

    public InstanceModel getOwner()

### setOwner

    protected void setOwner(InstanceModel owner)

### getLearnerMode

    public int getLearnerMode()

### setLearnerMode

    public void setLearnerMode(int learnerMode)
                        throws MaltChainedException

  Throws:
    `MaltChainedException`

### getLearningMethodName

    public String getLearningMethodName()

### getConfiguration

    public DependencyParserConfig getConfiguration()
                                            throws MaltChainedException

  Returns the current configuration

  Returns:
    the current configuration
  Throws:
    `MaltChainedException`

### getNumberOfInstances

    public int getNumberOfInstances()
                             throws MaltChainedException

  Throws:
    `MaltChainedException`

### increaseNumberOfInstances

    public void increaseNumberOfInstances()

  Specified by:
    `increaseNumberOfInstances` in interface `LearningMethod`

### decreaseNumberOfInstances

    public void decreaseNumberOfInstances()

  Specified by:
    `decreaseNumberOfInstances` in interface `LearningMethod`

### setNumberOfInstances

    protected void setNumberOfInstances(int numberOfInstances)

### setLearningMethodName

    protected void setLearningMethodName(String name)

### getInstanceOutputStreamWriter

    protected OutputStreamWriter getInstanceOutputStreamWriter(String suffix)
                                                        throws MaltChainedException

  Throws:
    `MaltChainedException`

### getInstanceInputStreamReader

    protected InputStreamReader getInstanceInputStreamReader(String suffix)
                                                      throws MaltChainedException

  Throws:
    `MaltChainedException`

### getInstanceInputStreamReaderFromConfigFile

    protected InputStreamReader getInstanceInputStreamReaderFromConfigFile(String suffix)
                                                                    throws MaltChainedException

  Throws:
    `MaltChainedException`

### getFile

    protected File getFile(String suffix)
                    throws MaltChainedException

  Throws:
    `MaltChainedException`

### getConfigFileEntry

    protected JarEntry getConfigFileEntry(String suffix)
                                   throws MaltChainedException

  Throws:
    `MaltChainedException`

### readLibLinearProblem

    public liblinear.Problem readLibLinearProblem(InputStreamReader isr,
                                                  int[] cardinalities)
                                           throws MaltChainedException

  Reads an instance file into a svm_problem object according to the Malt-SVM format, which is column fixed format (tab-separated).

  Parameters:
    `isr` - the instance stream reader for the instance file
    `cardinalities` - a array containing the number of distinct values for a particular column.
  Throws:
    `LiblinearException`
    `MaltChainedException`

### initSpecialParameters

    protected void initSpecialParameters()
                                  throws MaltChainedException

  Throws:
    `MaltChainedException`

### getLibLinearOptions

    public String getLibLinearOptions()

### parseParameters

    public void parseParameters(String paramstring)
                         throws MaltChainedException

  Throws:
    `MaltChainedException`

### getBias

    public double getBias()
                   throws MaltChainedException

  Throws:
    `MaltChainedException`

### getLiblinearParameters

    public liblinear.Parameter getLiblinearParameters()
                                               throws MaltChainedException

  Throws:
    `MaltChainedException`

### initLiblinearOptions

    public void initLiblinearOptions()

### getLibLinearParamStringArray

    public String[] getLibLinearParamStringArray()

### liblinear_predict_with_kbestlist

    public void liblinear_predict_with_kbestlist(liblinear.Model model,
                                                 liblinear.FeatureNode[] x,
                                                 KBestList kBestList)
                                          throws MaltChainedException

  Throws:
    `MaltChainedException`

### maltSVMFormat2OriginalSVMFormat

    public static void maltSVMFormat2OriginalSVMFormat(InputStreamReader isr,
                                                       OutputStreamWriter osw,
                                                       int[] cardinalities)
                                                throws MaltChainedException

  Converts the instance file (Malt's own SVM format) into the Liblinear (SVMLight) format. The input instance file is removed (replaced) by the instance file in the Liblinear (SVMLight) format. If a column contains -1, the value will be removed in destination file.

  Parameters:
    `isr` - the input stream reader for the source instance file
    `osw` - the output stream writer for the destination instance file
    `cardinalities` - a vector containing the number of distinct values for a particular column
  Throws:
    `LiblinearException`
    `MaltChainedException`

### finalize

    protected void finalize()
                     throws Throwable

  Overrides:
    `finalize` in class `Object`
  Throws:
    `Throwable`

### toString

    public String toString()

  Overrides:
    `toString` in class `Object`

### divideByFeatureSet

    public void divideByFeatureSet(Set<Integer> featureIdsToCreateSeparateBranchesForSet,
                                   ArrayList<Integer> divideFeatureIndexVector,
                                   String otherId)
                            throws MaltChainedException

  Specified by:
    `divideByFeatureSet` in interface `LearningMethod`
  Throws:
    `MaltChainedException`

### createFeatureIdToCountMap

    public Map<Integer,Integer> createFeatureIdToCountMap(ArrayList<Integer> divideFeatureIndexVector)
                                                   throws MaltChainedException

  Specified by:
    `createFeatureIdToCountMap` in interface `LearningMethod`
  Throws:
    `MaltChainedException`

Overview | Package | Class | Use | Tree | Deprecated | Index | Help
| MaltParser 1.4.1
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SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD

Copyright 2007-2010 Johan Hall, Jens Nilsson and Joakim Nivre.