org.allenai.nlpstack.parse.poly.fsm

DecisionTreeClassifier

Related Doc: package fsm

case class DecisionTreeClassifier(decisionTree: DecisionTree, transitions: IndexedSeq[StateTransition], featureNameMap: Seq[(Int, FeatureName)], numFeatures: Int) extends TransitionClassifier with Product with Serializable

A DecisionTreeClassifier wraps the org.allenai.nlpstack.parse.poly.decisiontree implementation to provide a classifier interface that maps Transitions to probabilities.

decisionTree

the underlying decision tree

featureNameMap

a list of the feature indices followed by their names

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Serializable, Serializable, Product, Equals, TransitionClassifier, AnyRef, Any
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Instance Constructors

  1. new DecisionTreeClassifier(decisionTree: DecisionTree, transitions: IndexedSeq[StateTransition], featureNameMap: Seq[(Int, FeatureName)], numFeatures: Int)

    decisionTree

    the underlying decision tree

    featureNameMap

    a list of the feature indices followed by their names

Value Members

  1. final def !=(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

    Definition Classes
    AnyRef → Any

  3. final def ==(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  4. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  5. def classify(featureVector: FeatureVector): StateTransition

    Returns the most probable Transition according to .getDistribution(featureVector).

    Returns the most probable Transition according to .getDistribution(featureVector).

    featureVector

    the feature vector to use to compute the distribution

    returns

    the most probable Transition, given the argument feature vector

    Definition Classes
    DecisionTreeClassifier → TransitionClassifier

  6. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  7. val decisionTree: DecisionTree

    the underlying decision tree

  8. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  9. val featureNameMap: Seq[(Int, FeatureName)]

    a list of the feature indices followed by their names

  10. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  11. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any

  12. def getDistribution(featureVector: FeatureVector): Map[StateTransition, Double]

    Given the argument feature vector, this assigns a probability to a set of Transitions.

    Given the argument feature vector, this assigns a probability to a set of Transitions.

    featureVector

    the feature vector to use to compute the distribution

    returns

    a probability distribution over Transitions

    Definition Classes
    DecisionTreeClassifier → TransitionClassifier

  13. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  14. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  15. final def notify(): Unit

    Definition Classes
    AnyRef

  16. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  17. val numFeatures: Int

  18. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef

  19. val transitions: IndexedSeq[StateTransition]

  20. final def wait(): Unit

    Definition Classes
    AnyRef
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    @throws( ... )

  21. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
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    @throws( ... )

  22. final def wait(arg0: Long): Unit

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Inherited from Serializable

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Inherited from Equals

Inherited from TransitionClassifier

Inherited from AnyRef

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