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## org.maltparser.parser.guide.instance
Class AtomicModel

    java.lang.Object
      org.maltparser.parser.guide.instance.AtomicModel

All Implemented Interfaces:
  InstanceModel, Model

    public class AtomicModel

extends Object
implements InstanceModel

Since:
  1.0
Author:
  Johan Hall

Constructor Summary
`AtomicModel(int index, FeatureVector features, Model parent)` Constructs an atomic model.

Method Summary
`void` | `addInstance(SingleDecision decision)`
`void` | `decreaseFrequency()`
`FeatureVector` | `extract()`
`void` | `finalizeSentence(DependencyStructure dependencyGraph)`
`FeatureVector` | `getFeatures()` Returns the feature vector used by this atomic model
`int` | `getFrequency()` Returns the frequency (number of instances)
`ClassifierGuide` | `getGuide()`
`int` | `getIndex()` Returns the index of the atomic model
`LearningMethod` | `getMethod()` Returns a learner object
`String` | `getModelName()`
`Model` | `getParent()` Returns the parent guide model
`void` | `increaseFrequency()` Increase the frequency by 1
`void` | `initMethod()` Initialize the learning method according to the option --learner-method.
`void` | `moveAllInstances(AtomicModel model, FeatureFunction divideFeature, ArrayList<Integer> divideFeatureIndexVector)` Moves all instance from this atomic model into the destination atomic model and add the divide feature.
`void` | `noMoreInstances()`
`boolean` | `predict(SingleDecision decision)`
`FeatureVector` | `predictExtract(SingleDecision decision)`
`protected void` | `setFeatures(FeatureVector features)` Sets the feature vector used by the atomic model.
`protected void` | `setFrequency(int frequency)` Sets the frequency (number of instances)
`protected void` | `setIndex(int index)` Sets the index of the model (-1..n), where -1 is a special value.
`protected void` | `setModelName(String modelName)` Sets the name of the atomic model
`protected void` | `setParent(Model parent)` Sets the parent guide model
`void` | `terminate()`
`String` | `toString()`
`void` | `train()` Invokes the train() of the learning method

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

Constructor Detail

### AtomicModel

    public AtomicModel(int index,
                       FeatureVector features,
                       Model parent)
                throws MaltChainedException

  Constructs an atomic model.

  Parameters:
    `index` - the index of the atomic model (-1..n), where -1 is special value (used by a single model or the master divide model) and n is number of divide models.
    `features` - the feature vector used by the atomic model.
    `parent` - the parent guide model.
  Throws:
    `MaltChainedException`

Method Detail

### addInstance

    public void addInstance(SingleDecision decision)
                     throws MaltChainedException

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

### noMoreInstances

    public void noMoreInstances()
                         throws MaltChainedException

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

### finalizeSentence

    public void finalizeSentence(DependencyStructure dependencyGraph)
                          throws MaltChainedException

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

### predict

    public boolean predict(SingleDecision decision)
                    throws MaltChainedException

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

### predictExtract

    public FeatureVector predictExtract(SingleDecision decision)
                                 throws MaltChainedException

  Specified by:
    `predictExtract` in interface `InstanceModel`
  Throws:
    `MaltChainedException`

### extract

    public FeatureVector extract()
                          throws MaltChainedException

  Specified by:
    `extract` in interface `InstanceModel`
  Throws:
    `MaltChainedException`

### terminate

    public void terminate()
                   throws MaltChainedException

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

### moveAllInstances

    public void moveAllInstances(AtomicModel model,
                                 FeatureFunction divideFeature,
                                 ArrayList<Integer> divideFeatureIndexVector)
                          throws MaltChainedException

  Moves all instance from this atomic model into the destination atomic model and add the divide feature. This method is used by the feature divide model to sum up all model below a certain threshold.

  Parameters:
    `model` - the destination atomic model
    `divideFeature` - the divide feature
    `divideFeatureIndexVector` - the divide feature index vector
  Throws:
    `MaltChainedException`

### train

    public void train()
               throws MaltChainedException

  Invokes the train() of the learning method

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

### initMethod

    public void initMethod()
                    throws MaltChainedException

  Initialize the learning method according to the option --learner-method.

  Throws:
    `MaltChainedException`

### getParent

    public Model getParent()
                    throws MaltChainedException

  Returns the parent guide model

  Returns:
    the parent guide model
  Throws:
    `MaltChainedException`

### setParent

    protected void setParent(Model parent)

  Sets the parent guide model

  Parameters:
    `parent` - the parent guide model

### getModelName

    public String getModelName()

  Specified by:
    `getModelName` in interface `Model`

### setModelName

    protected void setModelName(String modelName)

  Sets the name of the atomic model

  Parameters:
    `modelName` - the name of the atomic model

### getFeatures

    public FeatureVector getFeatures()

  Returns the feature vector used by this atomic model

  Returns:
    a feature vector object

### setFeatures

    protected void setFeatures(FeatureVector features)

  Sets the feature vector used by the atomic model.

  Parameters:
    `features` - a feature vector object

### getGuide

    public ClassifierGuide getGuide()

  Specified by:
    `getGuide` in interface `Model`

### getIndex

    public int getIndex()

  Returns the index of the atomic model

  Returns:
    the index of the atomic model

### setIndex

    protected void setIndex(int index)

  Sets the index of the model (-1..n), where -1 is a special value.

  Parameters:
    `index` - index value (-1..n) of the atomic model

### getFrequency

    public int getFrequency()

  Returns the frequency (number of instances)

  Returns:
    the frequency (number of instances)

### increaseFrequency

    public void increaseFrequency()

  Increase the frequency by 1

  Specified by:
    `increaseFrequency` in interface `InstanceModel`

### decreaseFrequency

    public void decreaseFrequency()

  Specified by:
    `decreaseFrequency` in interface `InstanceModel`

### setFrequency

    protected void setFrequency(int frequency)

  Sets the frequency (number of instances)

  Parameters:
    `frequency` - (number of instances)

### getMethod

    public LearningMethod getMethod()

  Returns a learner object

  Returns:
    a learner object

### toString

    public String toString()

  Overrides:
    `toString` in class `Object`

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Copyright 2007-2011 Johan Hall, Jens Nilsson and Joakim Nivre.