Class

ml.combust.mleap.runtime.transformer.regression

LinearRegression

Related Doc: package regression

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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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Inherited
  1. LinearRegression
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. Transformer
  7. AnyRef
  8. Any
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Visibility
  1. Public
  2. All

Instance Constructors

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

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    uid

    unique identifier

    featuresCol

    input column containing features

    predictionCol

    output column containing prediction

    model

    linear regression model

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. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  5. def clone(): AnyRef

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

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

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    Definition Classes
    AnyRef

  7. val exec: UserDefinedFunction

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  8. val featuresCol: String

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    input column containing features

  9. def finalize(): Unit

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

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

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    Definition Classes
    AnyRef → Any

  11. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  12. val model: LinearRegressionModel

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    linear regression model

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

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    Definition Classes
    AnyRef

  14. final def notify(): Unit

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    Definition Classes
    AnyRef

  15. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  16. val predictionCol: String

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    output column containing prediction

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

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    Definition Classes
    AnyRef

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

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    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

  19. val uid: String

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    unique identifier

    unique identifier

    Definition Classes
    LinearRegression → Transformer

  20. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    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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