ml.combust.mleap.core.regression

LinearRegressionModel

case class LinearRegressionModel(coefficients: Vector, intercept: Double) extends Model with Product with Serializable

Class for linear regression model.

coefficients

coefficients for linear regression

intercept

intercept for regression

Linear Supertypes
Serializable, Serializable, Product, Equals, Model, AnyRef, Any
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  1. LinearRegressionModel
  2. Serializable
  3. Serializable
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  6. Model
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Instance Constructors

  1. new LinearRegressionModel(coefficients: Vector, intercept: Double)

    coefficients

    coefficients for linear regression

    intercept

    intercept for regression

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. def apply(features: Vector): Double

    Alias for ml.combust.mleap.core.regression.LinearRegressionModel#predict

    Alias for ml.combust.mleap.core.regression.LinearRegressionModel#predict

    features

    features for prediction

    returns

    prediction

  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  8. def clone(): AnyRef

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

  9. val coefficients: Vector

    coefficients for linear regression

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

    Definition Classes
    AnyRef

  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. def inputSchema: StructType

    Definition Classes
    LinearRegressionModel → Model

  14. val intercept: Double

    intercept for regression

  15. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

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

    Definition Classes
    AnyRef

  17. final def notify(): Unit

    Definition Classes
    AnyRef

  18. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  19. def outputSchema: StructType

    Definition Classes
    LinearRegressionModel → Model

  20. def predict(features: Vector): Double

    Predict a value using this linear regression.

    Predict a value using this linear regression.

    features

    features for prediction

    returns

    prediction

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

    Definition Classes
    AnyRef

  22. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
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    @throws( ... )

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

    Definition Classes
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Inherited from Serializable

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Inherited from Product

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Inherited from Model

Inherited from AnyRef

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