Packages

case class LogRegRanker(train: Dataset, options: RegressionOptions) extends Ranker[LogRegModel] with Product with Serializable

Linear Supertypes
Serializable, Serializable, Product, Equals, Ranker[LogRegModel], Logging, AnyRef, Any
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Inherited
  1. LogRegRanker
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. Ranker
  7. Logging
  8. AnyRef
  9. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new LogRegRanker(train: Dataset, options: RegressionOptions)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native() @HotSpotIntrinsicCandidate()
  6. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  7. def fit(): LogRegModel
    Definition Classes
    LogRegRanker → Ranker
  8. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  9. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  10. val logger: Logger
    Definition Classes
    Logging
  11. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  12. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  13. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  14. val options: RegressionOptions
  15. def predict(row: RealVector, weights: RealVector, intercept: Double): Double
  16. def prepare(): (Array2DRowRealMatrix, ArrayRealVector)
  17. def randomSample(from: Int, to: Int, count: Int): Array[Int]
  18. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  19. val train: Dataset
  20. def trainBatchSGD(x: Array2DRowRealMatrix, y: RealVector, iterations: Int, batchSize: Int, lr: Double): RegWeights
  21. def trainSGD(x: Array2DRowRealMatrix, y: RealVector, iterations: Int, lr: Double): RegWeights
  22. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  23. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  24. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  25. val x: Array2DRowRealMatrix
  26. val y: ArrayRealVector

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] ) @Deprecated
    Deprecated

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from Ranker[LogRegModel]

Inherited from Logging

Inherited from AnyRef

Inherited from Any

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