Class

axle.ml

LinearRegression

Related Doc: package ml

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case class LinearRegression[D, M](examples: Seq[D], numFeatures: Int, featureExtractor: (D) ⇒ Seq[Double], objectiveExtractor: (D) ⇒ Double, α: Double = 0.1, iterations: Int = 100)(implicit la: LinearAlgebra[M, Int, Int, Double]) extends (D) ⇒ Double with Product with Serializable

Linear Supertypes
Serializable, Serializable, Product, Equals, (D) ⇒ Double, AnyRef, Any
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Inherited
  1. LinearRegression
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. Function1
  7. AnyRef
  8. Any
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Visibility
  1. Public
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Instance Constructors

  1. new LinearRegression(examples: Seq[D], numFeatures: Int, featureExtractor: (D) ⇒ Seq[Double], objectiveExtractor: (D) ⇒ Double, α: Double = 0.1, iterations: Int = 100)(implicit la: LinearAlgebra[M, Int, Int, Double])

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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 X: M

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  5. def andThen[A](g: (Double) ⇒ A): (D) ⇒ A

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    Definition Classes
    Function1
    Annotations
    @unspecialized()

  6. def apply(observation: D): Double

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    Definition Classes
    LinearRegression → Function1

  7. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  8. def clone(): AnyRef

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

  9. def compose[A](g: (A) ⇒ D): (A) ⇒ Double

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    Definition Classes
    Function1
    Annotations
    @unspecialized()

  10. def cost(xi: M, θ: M, yi: Double): Double

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  11. def dTheta(X: M, y: M, θ: M): M

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  12. def dθ(X: M, y: M, θ: M): M

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

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    Definition Classes
    AnyRef

  14. def errTree: TreeMap[Int, Double]

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  15. val errorLogReversed: List[Double]

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  16. val examples: Seq[D]

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  17. val featureExtractor: (D) ⇒ Seq[Double]

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  18. val featureNormalizer: LinearFeatureNormalizer[M]

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  19. def finalize(): Unit

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

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

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    Definition Classes
    AnyRef → Any

  21. def gradientDescent(X: M, y: M, θ: M, α: Double, iterations: Int): (M, List[Double])

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  22. def h(xi: M, θ: M): M

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  23. val inputX: M

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  24. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  25. val iterations: Int

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  26. implicit val module: Module[M, Double]

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

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    Definition Classes
    AnyRef

  28. def normalEquation(X: M, y: M): M

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  29. final def notify(): Unit

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    Definition Classes
    AnyRef

  30. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  31. val numFeatures: Int

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  32. val objectiveExtractor: (D) ⇒ Double

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  33. val objectiveNormalizer: LinearFeatureNormalizer[M]

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  34. implicit val ringM: Ring[M]

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

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    Definition Classes
    AnyRef

  36. def toString(): String

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    Definition Classes
    Function1 → AnyRef → Any

  37. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  40. val y: M

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  41. val α: Double

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  42. val θ: M

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  43. val θ0: M

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Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from (D) ⇒ Double

Inherited from AnyRef

Inherited from Any

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