Class

com.github.rzykov.fastml4j.metric

RegressionMetrics

Related Doc: package metric

Permalink

class RegressionMetrics extends AnyRef

Calculates regression metrics based on a comparison of real and predicted labels

Linear Supertypes
AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. RegressionMetrics
  2. AnyRef
  3. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new RegressionMetrics(realLabels: INDArray, predictedLabels: INDArray)

    Permalink

    realLabels

    NDArray of real labels

    predictedLabels

    NDArray of predicted lables

Value Members

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

    Permalink
    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

    Permalink
    Definition Classes
    AnyRef → Any

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

    Permalink
    Definition Classes
    AnyRef → Any

  4. final def asInstanceOf[T0]: T0

    Permalink
    Definition Classes
    Any

  5. def clone(): AnyRef

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

  6. lazy val differenceSumSquared: Float

    Permalink

    calculates sum of squared differences

  7. lazy val differenceVariance: Float

    Permalink

    calculates the variance of errors (differences)

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

    Permalink
    Definition Classes
    AnyRef

  9. def equals(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any

  10. def finalize(): Unit

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

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

    Permalink
    Definition Classes
    AnyRef → Any

  12. def hashCode(): Int

    Permalink
    Definition Classes
    AnyRef → Any

  13. final def isInstanceOf[T0]: Boolean

    Permalink
    Definition Classes
    Any

  14. lazy val meanAbsoluteError: Float

    Permalink

    Calculates Mean Absolute Error(MAE)

    Calculates Mean Absolute Error(MAE)

    returns

    MAE

  15. def meanSquaredError: Float

    Permalink

    Calculates MSE

    Calculates MSE

    returns

    MSE

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

    Permalink
    Definition Classes
    AnyRef

  17. final def notify(): Unit

    Permalink
    Definition Classes
    AnyRef

  18. final def notifyAll(): Unit

    Permalink
    Definition Classes
    AnyRef

  19. val predictedLabels: INDArray

    Permalink

    NDArray of predicted lables

  20. val realLabels: INDArray

    Permalink

    NDArray of real labels

  21. lazy val rootDifferenceSumSquared: Float

    Permalink

    calculates root of sum of squared differences

  22. def rootMeanSquaredError: Float

    Permalink

    Calculates RMSE

    Calculates RMSE

    returns

    RMSE

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

    Permalink
    Definition Classes
    AnyRef

  24. def toString(): String

    Permalink
    Definition Classes
    RegressionMetrics → AnyRef → Any

  25. final def wait(): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from AnyRef

Inherited from Any

Ungrouped