axle.ml

LinearRegressionModule

object LinearRegressionModule extends LinearRegressionModule

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  1. case class LinearEstimator[D](featureExtractor: (D) ⇒ List[Double], featureNormalizer: FeatureNormalizerModule.FeatureNormalizer, θ: matrix.JblasMatrixModule.Matrix[Double], objectiveNormalizer: FeatureNormalizerModule.FeatureNormalizer, errLog: List[Double]) extends Product with Serializable

    Definition Classes
    LinearRegressionModule

Value Members

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

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

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  3. final def ##(): Int

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

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

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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    protected[java.lang]
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    @throws()
  8. def cost(xi: matrix.JblasMatrixModule.Matrix[Double], θ: matrix.JblasMatrixModule.Matrix[Double], yi: Double): matrix.JblasMatrixModule.Matrix[Double]

    Definition Classes
    LinearRegressionModule
  9. def dTheta(X: matrix.JblasMatrixModule.Matrix[Double], y: matrix.JblasMatrixModule.Matrix[Double], θ: matrix.JblasMatrixModule.Matrix[Double]): matrix.JblasMatrixModule.Matrix[Double]

    Definition Classes
    LinearRegressionModule
  10. def (X: matrix.JblasMatrixModule.Matrix[Double], y: matrix.JblasMatrixModule.Matrix[Double], θ: matrix.JblasMatrixModule.Matrix[Double]): matrix.JblasMatrixModule.Matrix[Double]

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    LinearRegressionModule
  11. final def eq(arg0: AnyRef): Boolean

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  12. def equals(arg0: Any): Boolean

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  13. def finalize(): Unit

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

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  15. def gradientDescent(X: matrix.JblasMatrixModule.Matrix[Double], y: matrix.JblasMatrixModule.Matrix[Double], θ: matrix.JblasMatrixModule.Matrix[Double], α: Double, iterations: Int): (matrix.JblasMatrixModule.Matrix[Double], List[Double])

    Definition Classes
    LinearRegressionModule
  16. def h(xi: matrix.JblasMatrixModule.Matrix[Double], θ: matrix.JblasMatrixModule.Matrix[Double]): matrix.JblasMatrixModule.Matrix[Double]

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    LinearRegressionModule
  17. def hashCode(): Int

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  18. final def isInstanceOf[T0]: Boolean

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

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  20. def normalEquation(X: matrix.JblasMatrixModule.Matrix[Double], y: matrix.JblasMatrixModule.Matrix[Double]): matrix.JblasMatrixModule.Matrix[Double]

    Definition Classes
    LinearRegressionModule
  21. final def notify(): Unit

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  22. final def notifyAll(): Unit

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  23. def regression[D](examples: Seq[D], numFeatures: Int, featureExtractor: (D) ⇒ List[Double], objectiveExtractor: (D) ⇒ Double, α: Double, iterations: Int): LinearEstimator[D]

    Definition Classes
    LinearRegressionModule
  24. final def synchronized[T0](arg0: ⇒ T0): T0

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  25. def toString(): String

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  26. final def wait(): Unit

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

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

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