Uses of Class cc.mallet.types.FeatureSelection (Mallet 2 API)

Packages that use FeatureSelection
Package	Description
cc.mallet.classify	Classes for training and classifying instances.
cc.mallet.fst	Transducers, including Conditional Random Fields (CRFs).
cc.mallet.types	Fundamental MALLET types, including FeatureVector, Instance, Label etc.

Uses of FeatureSelection in cc.mallet.classify

Fields in cc.mallet.classify declared as FeatureSelection
Modifier and Type	Field	Description
`protected FeatureSelection`	MaxEnt.`featureSelection`
`protected FeatureSelection[]`	MaxEnt.`perClassFeatureSelection`

Methods in cc.mallet.classify that return FeatureSelection
Modifier and Type	Method	Description
`FeatureSelection`	Classifier.`getFeatureSelection()`
`FeatureSelection`	MaxEnt.`getFeatureSelection()`
`FeatureSelection[]`	Classifier.`getPerClassFeatureSelection()`
`FeatureSelection[]`	MaxEnt.`getPerClassFeatureSelection()`

Methods in cc.mallet.classify with parameters of type FeatureSelection
Modifier and Type	Method	Description
`void`	DecisionTree.Node.`induceFeatures(AugmentableFeatureVector afv, FeatureSelection featuresAlreadyThere, FeatureSelection[] perClassFeaturesAlreadyThere, FeatureSelection newFeatureSelection, FeatureSelection[] perClassNewFeatureSelection, boolean withInteriorNodes, boolean addPerClassFeatures, double classEntropyThreshold)`
`MaxEnt`	MaxEnt.`setFeatureSelection(FeatureSelection fs)`
`MaxEnt`	MaxEnt.`setPerClassFeatureSelection(FeatureSelection[] fss)`
`void`	DecisionTree.Node.`split(FeatureSelection fs)`
`protected void`	DecisionTreeTrainer.`splitTree(DecisionTree.Node node, FeatureSelection selectedFeatures, int depth)`

Constructors in cc.mallet.classify with parameters of type FeatureSelection
Constructor	Description
`MaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection)`
`MaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection[] perClassFeatureSelection)`
`MaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection, FeatureSelection[] perClassFeatureSelection)`
`MCMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection)`
`MCMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection[] perClassFeatureSelection)`
`MCMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection, FeatureSelection[] perClassFeatureSelection)`
`Node(InstanceList ilist, DecisionTree.Node parent, FeatureSelection fs)`
`RankMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection)`
`RankMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection[] perClassFeatureSelection)`
`RankMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection, FeatureSelection[] perClassFeatureSelection)`

Uses of FeatureSelection in cc.mallet.fst

Fields in cc.mallet.fst declared as FeatureSelection
Modifier and Type	Field	Description
`protected FeatureSelection[]`	CRF.`featureSelections`
`protected FeatureSelection`	CRF.`globalFeatureSelection`

Methods in cc.mallet.fst with parameters of type FeatureSelection
Modifier and Type	Method	Description
`void`	CRF.`setFeatureSelection(int weightIdx, FeatureSelection fs)`

Uses of FeatureSelection in cc.mallet.types

Methods in cc.mallet.types that return FeatureSelection
Modifier and Type	Method	Description
`static FeatureSelection`	FeatureSelection.`createFromRegex(Alphabet dictionary, java.util.regex.Pattern regex)`	Creates a FeatureSelection that includes only those features whose names match a given regex.
`FeatureSelection`	InstanceList.`getFeatureSelection()`
`FeatureSelection[]`	InstanceList.`getPerLabelFeatureSelection()`

Methods in cc.mallet.types with parameters of type FeatureSelection
Modifier and Type	Method	Description
`void`	FeatureConjunction.`addTo(AugmentableFeatureVector fv, double value, FeatureSelection fs)`
`void`	FeatureConjunction.List.`addTo(AugmentableFeatureVector fv, double value, FeatureSelection fs)`
`int`	RankedFeatureVector.`getMaxValuedIndexIn(FeatureSelection fs)`
`java.lang.Object`	RankedFeatureVector.`getMaxValuedObjectIn(FeatureSelection fs)`
`double`	RankedFeatureVector.`getMaxValueIn(FeatureSelection fs)`
`static FeatureVector`	FeatureVector.`newFeatureVector(FeatureVector fv, Alphabet newVocab, FeatureSelection fs)`	Construct a new FeatureVector, selecting only those features in fs, and having new (presumably more compact, dense) Alphabet.
`void`	FeatureSelection.`or(FeatureSelection fs)`
`static double`	MatrixOps.`rowDotProduct(double[] m, int nc, int ri, Vector v, double factor, int maxCi, FeatureSelection selection)`
`static double`	MatrixOps.`rowDotProduct(double[] m, int nc, int ri, Vector v, int maxCi, FeatureSelection selection)`
`static void`	MatrixOps.`rowSetAll(double[] m, int nc, int ri, double v, FeatureSelection fselection, boolean ifSelected)`	If "ifSelected" is false, it reverses the selection.
`void`	InstanceList.`setFeatureSelection(FeatureSelection selectedFeatures)`
`void`	InstanceList.`setPerLabelFeatureSelection(FeatureSelection[] selectedFeatures)`

Constructors in cc.mallet.types with parameters of type FeatureSelection
Constructor	Description
`FeatureVector(FeatureVector fv, Alphabet newVocab, FeatureSelection fsNarrow, FeatureSelection fsWide)`