ml.combust.mleap.runtime.transformer.regression

LinearRegression

case class LinearRegression(uid: String = ..., featuresCol: String, predictionCol: String, model: LinearRegressionModel) extends Transformer with Product with Serializable

Class for an MLeap linear regression transformer.

uid

unique identifier

featuresCol

input column containing features

predictionCol

output column containing prediction

model

linear regression model

Linear Supertypes
Serializable, Serializable, Product, Equals, Transformer, AnyRef, Any
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  1. LinearRegression
  2. Serializable
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Instance Constructors

  1. new LinearRegression(uid: String = ..., featuresCol: String, predictionCol: String, model: LinearRegressionModel)

    uid

    unique identifier

    featuresCol

    input column containing features

    predictionCol

    output column containing prediction

    model

    linear regression model

Value Members

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

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  6. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  7. def clone(): AnyRef

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

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

    Definition Classes
    AnyRef

  9. val exec: UserDefinedFunction

  10. val featuresCol: String

    input column containing features

  11. def finalize(): Unit

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

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

    Definition Classes
    AnyRef → Any

  13. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  14. val model: LinearRegressionModel

    linear regression model

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

    Definition Classes
    AnyRef

  16. final def notify(): Unit

    Definition Classes
    AnyRef

  17. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  18. val predictionCol: String

    output column containing prediction

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

    Definition Classes
    AnyRef

  20. def transform[TB <: TransformBuilder[TB]](builder: TB): Try[TB]

    Transform a builder using this MLeap transformer.

    Transform a builder using this MLeap transformer.

    TB

    underlying class of builder

    builder

    builder to transform

    returns

    try new builder with transformation applied

    Definition Classes
    LinearRegression → Transformer

  21. val uid: String

    unique identifier

    unique identifier

    Definition Classes
    LinearRegression → Transformer

  22. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  24. 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 Transformer

Inherited from AnyRef

Inherited from Any

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