BasicFeatureGenerator (Dragontool 1.3.3 API)

java.lang.Object
- dragon.ml.seqmodel.feature.BasicFeatureGenerator

All Implemented Interfaces:

FeatureGenerator
```
public class BasicFeatureGenerator
extends Object
implements FeatureGenerator
```
The FeatureGenerator is an aggregator over all these different feature types. You can inherit from the FeatureGenImpl class and after calling one of the constructors that does not make a call to (addFeatures()) you can then implement your own addFeatures class. There you will typically add the EdgeFeatures feature first and then the rest. So, for example if you wanted to add some parameter for each label (like a prior), you can create a new FeatureTypes class that will create as many featureids as the number of labels. This class is responsible for converting the string-ids that the FeatureTypes assign to their features into distinct numbers. It has a inner class called FeatureMap that will make one pass over the training data and create the map of featurenames->integer id and as a side effect count the number of features.

Author:

Sunita Sarawagi modified by davis

Field Summary

Fields
Modifier and Type	Field and Description
`protected int`	`curEndPos`
`protected FeatureType`	`currentFeatureType`
`protected DataSequence`	`curSeq`
`protected int`	`curStartPos`
`protected boolean`	`featureCollectingMode`
`protected Iterator`	`featureIter`
`protected FeatureMap`	`featureMap`
`protected Feature`	`featureToReturn`
`protected Vector`	`featureVector`
`protected ModelGraph`	`model`
`protected boolean`	`supportSegment`
`protected int`	`totalFeatures`

Constructor Summary

Constructors
Constructor and Description

BasicFeatureGenerator(ModelGraph model)

BasicFeatureGenerator(ModelGraph model, boolean supportSegment)

Constructors
Constructor and Description
`BasicFeatureGenerator(ModelGraph model)`
`BasicFeatureGenerator(ModelGraph model, boolean supportSegment)`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`boolean`	`addFeatureType(FeatureType fType)` Adds wanted feature type to the feature generator
`protected void`	`advance()`
`protected void`	`collectFeatureIdentifiers(Dataset trainData)`
`String`	`getFeatureName(int featureIndex)`
`int`	`getFeatureNum()`
`protected FeatureType`	`getFeatureType(int i)`
`FeatureType`	`getFeatureTYpe(int index)` Gets the index-th feature type
`int`	`getFeatureTypeNum()` Gets the number of wanted feature types.
`boolean`	`hasNext()` Tests if next feature exists
`protected void`	`initScanFeaturesAt(DataSequence d)`
`protected boolean`	`isValidFeature(DataSequence data, int curStartPos, int curEndPos, Feature featureToReturn)`
`boolean`	`loadFeatureData()` This method will be called in testing mode.
`Feature`	`next()` Gets the next feature.
`boolean`	`readFeatures(String fileName)` Reads feature list from a text file
`protected boolean`	`retainFeature(DataSequence seq, Feature f)`
`boolean`	`saveFeatures(String fileName)` Save features to a text file
`void`	`startScanFeaturesAt(DataSequence d, int startPos, int endPos)` Starts scanning features for the specified segment
`boolean`	`supportSegment()` Tests if the feature generatore supports the segment labeling problem
`boolean`	`train(Dataset trainData)` This method will be called in training mode.

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

- Field Detail
  - model
```
protected ModelGraph model
```
  - featureVector
```
protected Vector featureVector
```
  - featureIter
```
protected Iterator featureIter
```
  - currentFeatureType
```
protected FeatureType currentFeatureType
```
  - featureMap
```
protected FeatureMap featureMap
```
  - featureToReturn
```
protected Feature featureToReturn
```
  - curSeq
```
protected DataSequence curSeq
```
  - curStartPos
```
protected int curStartPos
```
  - curEndPos
```
protected int curEndPos
```
  - totalFeatures
```
protected int totalFeatures
```
  - featureCollectingMode
```
protected boolean featureCollectingMode
```
  - supportSegment
```
protected boolean supportSegment
```
- Constructor Detail
  - BasicFeatureGenerator
```
public BasicFeatureGenerator(ModelGraph model)
```
  - BasicFeatureGenerator
```
public BasicFeatureGenerator(ModelGraph model,
                             boolean supportSegment)
```
- Method Detail
  - supportSegment
```
public boolean supportSegment()
```
    Description copied from interface: FeatureGenerator
    
    Tests if the feature generatore supports the segment labeling problem
    
    Specified by:
    
    supportSegment in interface FeatureGenerator
    
    Returns:
    
    true if supported
  - addFeatureType
```
public boolean addFeatureType(FeatureType fType)
```
    Description copied from interface: FeatureGenerator
    
    Adds wanted feature type to the feature generator
    
    Specified by:
    
    addFeatureType in interface FeatureGenerator
    
    Parameters:
    
    fType - the wanted feature type
    
    Returns:
    
    true if added successfully
  - getFeatureTypeNum
```
public int getFeatureTypeNum()
```
    Description copied from interface: FeatureGenerator
    
    Gets the number of wanted feature types.
    
    Specified by:
    
    getFeatureTypeNum in interface FeatureGenerator
    
    Returns:
    
    the number of wanted feature types.
  - getFeatureTYpe
```
public FeatureType getFeatureTYpe(int index)
```
    Description copied from interface: FeatureGenerator
    
    Gets the index-th feature type
    
    Specified by:
    
    getFeatureTYpe in interface FeatureGenerator
    
    Parameters:
    
    index - the index of the feature type
    
    Returns:
    
    the index-th feature type
  - getFeatureType
```
protected FeatureType getFeatureType(int i)
```
  - train
```
public boolean train(Dataset trainData)
```
    Description copied from interface: FeatureGenerator
    
    This method will be called in training mode. The training procedure will build a index of all possible features. It will also train each feature type if necessary.
    
    Specified by:
    
    train in interface FeatureGenerator
    
    Parameters:
    
    trainData - the dataset for training
    
    Returns:
    
    true if trained successfully
  - loadFeatureData
```
public boolean loadFeatureData()
```
    Description copied from interface: FeatureGenerator
    
    This method will be called in testing mode. The related data for wanted feature types will be loaded. Actually this method will call the readTrainingResult method of each wanted feature type.
    
    Specified by:
    
    loadFeatureData in interface FeatureGenerator
    
    Returns:
    
    true if data is loaded successfully
  - collectFeatureIdentifiers
```
protected void collectFeatureIdentifiers(Dataset trainData)
```
  - advance
```
protected void advance()
```
  - isValidFeature
```
protected boolean isValidFeature(DataSequence data,
                                 int curStartPos,
                                 int curEndPos,
                                 Feature featureToReturn)
```
  - retainFeature
```
protected boolean retainFeature(DataSequence seq,
                                Feature f)
```
  - initScanFeaturesAt
```
protected void initScanFeaturesAt(DataSequence d)
```
  - startScanFeaturesAt
```
public void startScanFeaturesAt(DataSequence d,
                                int startPos,
                                int endPos)
```
    Description copied from interface: FeatureGenerator
    
    Starts scanning features for the specified segment
    
    Specified by:
    
    startScanFeaturesAt in interface FeatureGenerator
    
    Parameters:
    
    d - the sequence data
    
    startPos - the start position of the segment
    
    endPos - the end position of the segment
  - hasNext
```
public boolean hasNext()
```
    Description copied from interface: FeatureGenerator
    
    Tests if next feature exists
    
    Specified by:
    
    hasNext in interface FeatureGenerator
    
    Returns:
    
    true if next feature exist.
  - next
```
public Feature next()
```
    Description copied from interface: FeatureGenerator
    
    Gets the next feature.
    
    Specified by:
    
    next in interface FeatureGenerator
    
    Returns:
    
    next feature
  - getFeatureNum
```
public int getFeatureNum()
```
    Specified by:
    
    getFeatureNum in interface FeatureGenerator
    
    Returns:
    
    the number of unique features
  - getFeatureName
```
public String getFeatureName(int featureIndex)
```
    Specified by:
    
    getFeatureName in interface FeatureGenerator
    
    Parameters:
    
    featureIndex - the index of the feature
    
    Returns:
    
    the name of the feature
  - readFeatures
```
public boolean readFeatures(String fileName)
```
    Description copied from interface: FeatureGenerator
    
    Reads feature list from a text file
    
    Specified by:
    
    readFeatures in interface FeatureGenerator
    
    Parameters:
    
    fileName - the name of the file containing the feature information
    
    Returns:
    
    true if read successfully
  - saveFeatures
```
public boolean saveFeatures(String fileName)
```
    Description copied from interface: FeatureGenerator
    
    Save features to a text file
    
    Specified by:
    
    saveFeatures in interface FeatureGenerator
    
    Parameters:
    
    fileName - the name of the file all features will be save to
    
    Returns:
    
    true if saved successfully

Class BasicFeatureGenerator

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

model

featureVector

featureIter

currentFeatureType

featureMap

featureToReturn

curSeq

curStartPos

curEndPos

totalFeatures

featureCollectingMode

supportSegment

Constructor Detail

BasicFeatureGenerator

BasicFeatureGenerator

Method Detail

supportSegment

addFeatureType

getFeatureTypeNum

getFeatureTYpe

getFeatureType

train

loadFeatureData

collectFeatureIdentifiers

advance

isValidFeature

retainFeature

initScanFeaturesAt

startScanFeaturesAt

hasNext

next

getFeatureNum

getFeatureName

readFeatures

saveFeatures