dragon.ml.seqmodel.feature

Interface FeatureType

All Known Implementing Classes:

AbstractFeatureType, AbstractFeatureTypeWrapper, FeatureTypeConcatRegex, FeatureTypeEdge, FeatureTypeEnd, FeatureTypeKnownWord, FeatureTypePosition, FeatureTypePOSPattern, FeatureTypePrior, FeatureTypeRegexCount, FeatureTypeSegmentLength, FeatureTypeSegmentLengthPoly, FeatureTypeStart, FeatureTypeStateLoop, FeatureTypeTokenLoop, FeatureTypeUnknownWord, FeatureTypeWindow, FeatureTypeWord, FeatureTypeWordScore

public interface FeatureType

Interface of feature type which is actually a factory generating certain type of features

Copyright: Copyright (c) 2005

Company: IST, Drexel University

Version:

1.0

Author:

Davis Zhou

Method Summary

Modifier and Type	Method and Description
int	getTypeID() Gets the unique id of the current feature type.
boolean	hasNext() Tests if next feature exists
boolean	needTraining() Tests if the current feature type needs training
Feature	next() Gets the next feature
boolean	readTrainingResult() Reads the training result in testing mode
boolean	saveTrainingResult() Saves the training results in training mode
void	setTypeID(int typeID) Sets the id of the current feature type
boolean	startScanFeaturesAt(DataSequence seq, int startPos, int endPos) Starts scanning features of the given segment of a sequence
boolean	supportSegment() Tests if the feature type supports generating features for segments.
boolean	train(Dataset dataset) Trains the feature types with the labeled training dataset

Method Detail

startScanFeaturesAt

boolean startScanFeaturesAt(DataSequence seq,
                            int startPos,
                            int endPos)

Starts scanning features of the given segment of a sequence

Parameters:

seq - the sequence

startPos - the start position of the segment

endPos - the end position of the segment

Returns:

true if successfully

hasNext

boolean hasNext()

Tests if next feature exists

Returns:

true if next feature exists

next

Feature next()

Gets the next feature

Returns:

the next feature if any

needTraining

boolean needTraining()

Tests if the current feature type needs training

Returns:

true if the feature type needs training

train

boolean train(Dataset dataset)

Trains the feature types with the labeled training dataset

Parameters:

dataset - the dataset for training

Returns:

true if trained successfully

saveTrainingResult

boolean saveTrainingResult()

Saves the training results in training mode

Returns:

true if saved successfully

readTrainingResult

boolean readTrainingResult()

Reads the training result in testing mode

Returns:

training result

getTypeID

int getTypeID()

Gets the unique id of the current feature type.

Returns:

type ID

setTypeID

void setTypeID(int typeID)

Sets the id of the current feature type

Parameters:

typeID - the type id

supportSegment

boolean supportSegment()

Tests if the feature type supports generating features for segments.

Returns:

true if supported