Packages

c

io.citrine.lolo.hypers

RandomHyperOptimizer

class RandomHyperOptimizer extends HyperOptimizer

Search for hypers by randomly sampling the search space

This optimizer can be evaluated multiple times and will persist the best results across those calls. Created by maxhutch on 12/7/16.

Linear Supertypes
HyperOptimizer, AnyRef, Any
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Instance Constructors

  1. new RandomHyperOptimizer()

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. def addHyperGrid(name: String, values: Seq[Any]): RandomHyperOptimizer.this.type

    Add a 1D hyper range to the space searched by this optimizer

    Add a 1D hyper range to the space searched by this optimizer

    name

    of the hyper

    values

    it takes, enumerated as a seq

    returns

    calling instance

    Definition Classes
    HyperOptimizer
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. var best: Map[String, Any]

    Keep track of the best hypers outside of the optimize call so it persists across calls

  7. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )
  8. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  9. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  10. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  11. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  12. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  13. var hyperGrids: Map[String, Seq[Any]]

    The search space

    The search space

    Definition Classes
    HyperOptimizer
  14. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  15. var loss: Double

    Likewise with the lowest loss

  16. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  17. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  18. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  19. def optimize(trainingData: Seq[(Vector[Any], Any)], numIterations: Int, builder: (Map[String, Any]) ⇒ Learner): (Map[String, Any], Double)

    Search over numIterations random draws for the search space

    Search over numIterations random draws for the search space

    trainingData

    the data to train/test on

    numIterations

    number of draws to take

    returns

    the best hyper map found in give iterations and the corresponding loss

    Definition Classes
    RandomHyperOptimizer → HyperOptimizer
  20. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  21. def toString(): String
    Definition Classes
    AnyRef → Any
  22. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  23. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  24. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )

Inherited from HyperOptimizer

Inherited from AnyRef

Inherited from Any

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