org.allenai.nlpstack.parse.poly.decisiontree

SparseVector

Related Doc: package decisiontree

case class SparseVector(outcome: Option[Int], numFeatures: Int, trueFeatures: Set[Int]) extends FeatureVector with Product with Serializable

A SparseVector is a feature vector with sparse binary features.

outcome

the outcome of the feature vector

numFeatures

the number of features

trueFeatures

the set of features with value 1

Linear Supertypes
Serializable, Serializable, Product, Equals, FeatureVector, AnyRef, Any
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  1. SparseVector
  2. Serializable
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Instance Constructors

  1. new SparseVector(outcome: Option[Int], numFeatures: Int, trueFeatures: Set[Int])

    outcome

    the outcome of the feature vector

    numFeatures

    the number of features

    trueFeatures

    the set of features with value 1

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 clone(): AnyRef

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

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

    Definition Classes
    AnyRef

  7. def finalize(): Unit

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

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

    Definition Classes
    AnyRef → Any

  9. def getFeature(i: Int): Int

    Gets the value of the specified feature.

    Gets the value of the specified feature.

    returns

    the feature value

    Definition Classes
    SparseVector → FeatureVector

  10. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  11. def modifyOutcome(newLabel: Int): FeatureVector

    Returns a copy of this feature vector, associated with a different outcome.

    Returns a copy of this feature vector, associated with a different outcome.

    returns

    a copy of this feature vector, associated with a different outcome.

    Definition Classes
    SparseVector → FeatureVector

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

    Definition Classes
    AnyRef

  13. def nonzeroFeatures: Iterator[Int]

    Returns an iterator over all non-zero features in this feature vector.

    Returns an iterator over all non-zero features in this feature vector.

    Definition Classes
    SparseVector → FeatureVector

  14. final def notify(): Unit

    Definition Classes
    AnyRef

  15. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  16. val numFeatures: Int

    the number of features

    the number of features

    Definition Classes
    SparseVector → FeatureVector

  17. val outcome: Option[Int]

    the outcome of the feature vector

    the outcome of the feature vector

    Definition Classes
    SparseVector → FeatureVector

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

    Definition Classes
    AnyRef

  19. val trueFeatures: Set[Int]

    the set of features with value 1

  20. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from FeatureVector

Inherited from AnyRef

Inherited from Any

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