MaltParser 1.4.1

org.maltparser.ml
Interface LearningMethod

All Known Implementing Classes:
Liblinear, Libsvm

public interface LearningMethod


Field Summary
static int BATCH
           
static int CLASSIFY
           
 
Method Summary
 void addInstance(SingleDecision decision, FeatureVector featureVector)
           
 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)
           
 void finalizeSentence(DependencyStructure dependencyGraph)
           
 BufferedWriter getInstanceWriter()
           
 void increaseNumberOfInstances()
           
 void moveAllInstances(LearningMethod method, FeatureFunction divideFeature, ArrayList<Integer> divideFeatureIndexVector)
           
 void noMoreInstances()
           
 boolean predict(FeatureVector features, SingleDecision decision)
           
 void terminate()
           
 void train(FeatureVector featureVector)
           
 

Field Detail

BATCH

static final int BATCH
See Also:
Constant Field Values

CLASSIFY

static final int CLASSIFY
See Also:
Constant Field Values
Method Detail

addInstance

void addInstance(SingleDecision decision,
                 FeatureVector featureVector)
                 throws MaltChainedException
Throws:
MaltChainedException

finalizeSentence

void finalizeSentence(DependencyStructure dependencyGraph)
                      throws MaltChainedException
Throws:
MaltChainedException

noMoreInstances

void noMoreInstances()
                     throws MaltChainedException
Throws:
MaltChainedException

train

void train(FeatureVector featureVector)
           throws MaltChainedException
Throws:
MaltChainedException

crossValidate

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

Parameters:
featureVector -
nrOfSplits -
Returns:
a double
Throws:
MaltChainedException

moveAllInstances

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

terminate

void terminate()
               throws MaltChainedException
Throws:
MaltChainedException

predict

boolean predict(FeatureVector features,
                SingleDecision decision)
                throws MaltChainedException
Throws:
MaltChainedException

getInstanceWriter

BufferedWriter getInstanceWriter()

increaseNumberOfInstances

void increaseNumberOfInstances()

decreaseNumberOfInstances

void decreaseNumberOfInstances()

divideByFeatureSet

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

createFeatureIdToCountMap

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

MaltParser 1.4.1

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