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## Uses of Class
cc.mallet.types.FeatureSelection

Packages that use FeatureSelection
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
`protected FeatureSelection` | `MaxEnt.featureSelection`
`protected FeatureSelection[]` | `MaxEnt.perClassFeatureSelection`

Methods in cc.mallet.classify that return FeatureSelection
`FeatureSelection` | `MaxEnt.getFeatureSelection()`
`FeatureSelection` | `Classifier.getFeatureSelection()`
`FeatureSelection[]` | `MaxEnt.getPerClassFeatureSelection()`
`FeatureSelection[]` | `Classifier.getPerClassFeatureSelection()`

Methods in cc.mallet.classify with parameters of type FeatureSelection
`void` | `DecisionTree.Node.induceFeatures(AugmentableFeatureVector afv, FeatureSelection featuresAlreadyThere, FeatureSelection[] perClassFeaturesAlreadyThere, FeatureSelection newFeatureSelection, FeatureSelection[] perClassNewFeatureSelection, boolean withInteriorNodes, boolean addPerClassFeatures, double classEntropyThreshold)`
`void` | `DecisionTree.Node.induceFeatures(AugmentableFeatureVector afv, FeatureSelection featuresAlreadyThere, FeatureSelection[] perClassFeaturesAlreadyThere, FeatureSelection newFeatureSelection, FeatureSelection[] perClassNewFeatureSelection, boolean withInteriorNodes, boolean addPerClassFeatures, double classEntropyThreshold)`
`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
`DecisionTree.Node(InstanceList ilist, DecisionTree.Node parent, FeatureSelection fs)`
`MaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection)`
`MaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection[] perClassFeatureSelection)`
`MaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection, 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)`
`MCMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection, FeatureSelection[] perClassFeatureSelection)`
`RankMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection)`
`RankMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection[] perClassFeatureSelection)`
`RankMaxEnt(Pipe dataPipe, double[] parameters, FeatureSelection featureSelection, 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
`protected FeatureSelection[]` | `CRF.featureSelections`
`protected FeatureSelection` | `CRF.globalFeatureSelection`

Methods in cc.mallet.fst with parameters of type FeatureSelection
`void` | `CRF.setFeatureSelection(int weightIdx, FeatureSelection fs)`

Uses of FeatureSelection in cc.mallet.types

Methods in cc.mallet.types that return FeatureSelection
`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
`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)`
`double` | `Matrix2.rowDotProduct(int ri, Vector v, int maxCi, FeatureSelection selection)` Deprecated. Skip all column indices higher than "maxCi".
`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` | `Matrix2.rowSetAll(int ri, double v, FeatureSelection fselection, boolean ifSelected)` Deprecated. If "ifSelected" is false, it reverses the selection.
`void` | `Matrix2.setAll(double v, FeatureSelection fselection, boolean ifSelected)` Deprecated. 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
`FeatureVector(FeatureVector fv, Alphabet newVocab, FeatureSelection fsNarrow, FeatureSelection fsWide)`

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