c

io.citrine.lolo.linear

GuessTheMeanLearner

case class GuessTheMeanLearner(rng: Random = Random) extends Learner with Product with Serializable

Created by maxhutch on 11/15/16.

Linear Supertypes
Product, Equals, Learner, Serializable, AnyRef, Any
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Inherited
  1. GuessTheMeanLearner
  2. Product
  3. Equals
  4. Learner
  5. Serializable
  6. AnyRef
  7. Any
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Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new GuessTheMeanLearner(rng: Random = Random)

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[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native()
  6. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  7. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable])
  8. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  9. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  10. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  11. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  12. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  13. def productElementNames: Iterator[String]
    Definition Classes
    Product
  14. val rng: Random
  15. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  16. def train(trainingData: Seq[(Vector[Any], Any)], weights: Option[Seq[Double]]): TrainingResult

    Train a model

    Train a model

    trainingData

    to train on

    weights

    for the training rows, if applicable

    returns

    training result containing a model

    Definition Classes
    GuessTheMeanLearnerLearner
  17. def train(trainingData: Seq[(Vector[Any], Any, Double)]): TrainingResult

    Train a model with weights

    Train a model with weights

    trainingData

    with weights in the form (features, label, weight)

    returns

    training result containing a model

    Definition Classes
    Learner
  18. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  19. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  20. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()

Inherited from Product

Inherited from Equals

Inherited from Learner

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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