Class/Object

org.clulab.learning

LiblinearRegression

Related Docs: object LiblinearRegression | package learning

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class LiblinearRegression[F] extends Regression[F] with Serializable

Wrapper for liblinear regression, including LR and linear SVM User: mihais, danebell Date: 11/15/17

Linear Supertypes
Serializable, Regression[F], AnyRef, Any
Known Subclasses
L1LinearSVMRegression, LinearSVMRegression, LinearSVMRegressionDual
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Inherited
  1. LiblinearRegression
  2. Serializable
  3. Regression
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Visibility
  1. Public
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Instance Constructors

  1. new LiblinearRegression(solverType: SolverType = SolverType.L2R_L2LOSS_SVR, C: Double = 1.0, eps: Double = 0.01, p: Double = 0.1, bias: Boolean = false)

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Value Members

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

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    AnyRef → Any

  4. val C: Double

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  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  6. val bias: Boolean

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  7. def clone(): AnyRef

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

  8. val eps: Double

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

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    Definition Classes
    AnyRef

  10. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  11. def finalize(): Unit

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

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

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    Definition Classes
    AnyRef → Any

  13. def getWeights(verbose: Boolean = false): Counter[F]

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  14. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  15. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    AnyRef

  17. final def notify(): Unit

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    Definition Classes
    AnyRef

  18. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  19. val p: Double

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  20. def saveTo(w: Writer): Unit

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    Saves the current model to a file

    Saves the current model to a file

    Definition Classes
    LiblinearRegression → Regression

  21. def saveTo(fileName: String): Unit

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    Saves the current model to a file

    Saves the current model to a file

    Definition Classes
    Regression

  22. def scoreOf(d: Datum[Double, F]): Double

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    Returns the score for this datum NB: This is not necessarily a probability

    Returns the score for this datum NB: This is not necessarily a probability

    Definition Classes
    LiblinearRegression → Regression

  23. val solverType: SolverType

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

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    Definition Classes
    AnyRef

  25. def toString(): String

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    Definition Classes
    AnyRef → Any

  26. def train(dataset: RegDataset[F], indices: Array[Int]): Unit

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    Trains a classifier, using only the datums specified in indices indices is useful for bagging

    Trains a classifier, using only the datums specified in indices indices is useful for bagging

    Definition Classes
    LiblinearRegression → Regression

  27. def train(dataset: RegDataset[F], spans: Option[Iterable[(Int, Int)]]): Unit

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    Trains the classifier on the given dataset spans is useful during cross validation

    Trains the classifier on the given dataset spans is useful during cross validation

    Definition Classes
    Regression

  28. def train(dataset: RegDataset[F]): Unit

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    Definition Classes
    Regression

  29. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
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    Annotations
    @throws( ... )

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

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    Definition Classes
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    Annotations
    @throws( ... )

Inherited from Serializable

Inherited from Regression[F]

Inherited from AnyRef

Inherited from Any

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