calhoun.analysis.crf.features.tricycle13
Class EmissionMarkovFeature

java.lang.Object
  calhoun.analysis.crf.AbstractFeatureManager<java.lang.Character>
      calhoun.analysis.crf.features.tricycle13.EmissionMarkovFeature

All Implemented Interfaces:

FeatureManager<java.lang.Character>, FeatureManagerNode<java.lang.Character>, java.io.Serializable

public class EmissionMarkovFeature
extends AbstractFeatureManager<java.lang.Character>
implements FeatureManagerNode<java.lang.Character>

See Also:

Serialized Form

Nested Class Summary

static class

EmissionMarkovFeature.MarkovHistory

Constructor Summary

EmissionMarkovFeature()

EmissionMarkovFeature(java.util.List<int[]> history)

EmissionMarkovFeature(java.util.List<int[]> history, java.util.List<int[]> flags)

Method Summary

void	evaluateNode(InputSequence<? extends java.lang.Character> seq, int pos, int state, FeatureList result) Evaluates the set of features managed by this object for the given arguments.
CacheStrategySpec	getCacheStrategy() caching strategy that the CacheProcessor should use to cache values for this feature.
java.lang.String	getFeatureName(int featureIndex) Returns a human identifiable name for the feature referenced by a given index.
int	getNumFeatures() Returns the number of features maintained by this FeatureManager.
void	setHistory(EmissionMarkovFeature.MarkovHistory markovHistory)
void	train(int startingIndex, ModelManager modelInfo, java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data) Provides access to the entire training set so that FeatureManager can compute global properties and assign feature indices.

Methods inherited from class calhoun.analysis.crf.AbstractFeatureManager

getInputComponent, setInputComponent

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface calhoun.analysis.crf.FeatureManager

getInputComponent, setInputComponent

Constructor Detail

EmissionMarkovFeature

public EmissionMarkovFeature()

EmissionMarkovFeature

public EmissionMarkovFeature(java.util.List<int[]> history)

EmissionMarkovFeature

public EmissionMarkovFeature(java.util.List<int[]> history,
                             java.util.List<int[]> flags)

Method Detail

setHistory

public void setHistory(EmissionMarkovFeature.MarkovHistory markovHistory)

getNumFeatures

public int getNumFeatures()

Description copied from interface: FeatureManager

Returns the number of features maintained by this FeatureManager. This number must be fixed after the call to trainFeatures is complete.

Specified by:

getNumFeatures in interface FeatureManager<java.lang.Character>

Returns:

number of features managed by this FeatureManager

getFeatureName

public java.lang.String getFeatureName(int featureIndex)

Description copied from interface: FeatureManager

Returns a human identifiable name for the feature referenced by a given index. Used for display purposes only.

Specified by:

getFeatureName in interface FeatureManager<java.lang.Character>

Parameters:

featureIndex - the index of this feature

Returns:

the human readable name of this feature

evaluateNode

public void evaluateNode(InputSequence<? extends java.lang.Character> seq,
                         int pos,
                         int state,
                         FeatureList result)

Description copied from interface: FeatureManagerNode

Evaluates the set of features managed by this object for the given arguments.

Specified by:

evaluateNode in interface FeatureManagerNode<java.lang.Character>

train

public void train(int startingIndex,
                  ModelManager modelInfo,
                  java.util.List<? extends TrainingSequence<? extends java.lang.Character>> data)

Description copied from interface: FeatureManager

Provides access to the entire training set so that FeatureManager can compute global properties and assign feature indices. This will be called before any evaluations are requested. If the FeatureManager can have a variable number of features, this must be fixed within this method.

Specified by:

train in interface FeatureManager<java.lang.Character>

Parameters:

startingIndex - the feature index of the first feature owned by this FeatureManager. Each FeatureManager must use up consecutive indexes, so the last index used will be startingIndex + numFeatures - 1.

modelInfo - the model that contains this feature

data - the full list of training sequences to use to train the feature

getCacheStrategy

public CacheStrategySpec getCacheStrategy()

Description copied from interface: FeatureManager

caching strategy that the CacheProcessor should use to cache values for this feature. This is only a hint, the cache processor is not required to use this (or any) caching strategy. This base class defaults to the UNSPECIFIED cache strategy.

Specified by:

getCacheStrategy in interface FeatureManager<java.lang.Character>

Overrides:

getCacheStrategy in class AbstractFeatureManager<java.lang.Character>

Returns:

cache strategy specification appropriate for this feature.