org.allenai.nlpstack.core.conf.impl

LogisticRegression

Related Docs: object LogisticRegression | package impl

class LogisticRegression[T] extends ConfidenceFunction[T]

An implementation of logistic regression of features that can be represented as a double.

Linear Supertypes
ConfidenceFunction[T], (T) ⇒ Double, AnyRef, Any
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  1. LogisticRegression
  2. ConfidenceFunction
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Instance Constructors

  1. new LogisticRegression(featureSet: FeatureSet[T, Double], weights: Map[String, Double])

  2. new LogisticRegression(featureSet: FeatureSet[T, Double], featureWeights: Map[String, Double], intercept: Double)

    featureSet

    the features to use

    featureWeights

    the feature weights

    intercept

    the intercept value

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. def andThen[A](g: (Double) ⇒ A): (T) ⇒ A

    Definition Classes
    Function1
    Annotations
    @unspecialized()

  5. def apply(extraction: T): Double

    Definition Classes
    LogisticRegression → ConfidenceFunction → Function1

  6. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  7. def clone(): AnyRef

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

  8. def compose[A](g: (A) ⇒ T): (A) ⇒ Double

    Definition Classes
    Function1
    Annotations
    @unspecialized()

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

    Definition Classes
    AnyRef

  10. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  11. val featureSet: FeatureSet[T, Double]

    the features to use

    the features to use

    Definition Classes
    ConfidenceFunction

  12. val featureWeights: Map[String, Double]

    the feature weights

  13. def finalize(): Unit

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

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

    Definition Classes
    AnyRef → Any

  15. def getConf(extraction: T): Double

  16. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  17. val intercept: Double

    the intercept value

  18. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

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

    Definition Classes
    AnyRef

  20. final def notify(): Unit

    Definition Classes
    AnyRef

  21. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  22. def save(writer: PrintWriter): Unit

  23. def save(output: OutputStream): Unit

    Definition Classes
    LogisticRegression → ConfidenceFunction

  24. def saveFile(file: File): Unit

    Definition Classes
    ConfidenceFunction

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

    Definition Classes
    AnyRef

  26. def toString(): String

    Definition Classes
    Function1 → AnyRef → Any

  27. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from ConfidenceFunction[T]

Inherited from (T) ⇒ Double

Inherited from AnyRef

Inherited from Any

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