RandomSearch

Instance Constructors

new RandomSearch(numParams: Int, evaluationFunction: EvaluationFunction[T], discreteParams: Map[Int, Int] = Map(), kernel: StationaryKernel = new Matern52, seed: Long = System.currentTimeMillis)

numParams
The dimensionality of the hyper-parameter tuning problem
evaluationFunction
The function that evaluates points in the space to real values
discreteParams
Specifies the indices of discrete parameters and their numbers of discrete values
kernel
Specifies the indices and transformation function of hyper-parameters
seed
A random seed

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
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final def ##(): Int

Definition Classes
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final def ==(arg0: Any): Boolean

Definition Classes
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final def asInstanceOf[T0]: T0

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def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
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Annotations
@throws( ... )
def discretizeCandidate(candidate: DenseVector[Double], discreteParams: Map[Int, Int]): DenseVector[Double]

Discretize candidates with specified indices.
Discretize candidates with specified indices.
candidate
candidate with values in [0, 1]
discreteParams
Map that specifies the indices of discrete parameters and their numbers of discrete values
returns
candidate with the specified discrete values

Attributes
protected[com.linkedin.photon.ml.hyperparameter.search]
def drawCandidates(n: Int): DenseMatrix[Double]

Draw candidates from the distributions along each dimension in the space
Draw candidates from the distributions along each dimension in the space
n
the number of candidates to draw

Attributes
protected[com.linkedin.photon.ml.hyperparameter.search]
final def eq(arg0: AnyRef): Boolean

Definition Classes
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def equals(arg0: Any): Boolean

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def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
def find(n: Int): Seq[T]

Searches and returns n points in the space.
Searches and returns n points in the space.
n
The number of points to find
returns
The found points
def findWithPriorObservations(n: Int, priorObservations: Seq[(DenseVector[Double], Double)]): Seq[T]

Searches and returns n points in the space, given prior observations from past data sets.
Searches and returns n points in the space, given prior observations from past data sets.
n
The number of points to find
priorObservations
Observations made prior to searching, from past data sets (mean-centered)
returns
The found points
def findWithPriors(n: Int, observations: Seq[(DenseVector[Double], Double)], priorObservations: Seq[(DenseVector[Double], Double)]): Seq[T]

Searches and returns n points in the space, given prior observations from this data set and past data sets.
Searches and returns n points in the space, given prior observations from this data set and past data sets.
n
The number of points to find
observations
Observations made prior to searching, from this data set (not mean-centered)
priorObservations
Observations made prior to searching, from past data sets (mean-centered)
returns
The found points
final def getClass(): Class[_]

Definition Classes
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def hashCode(): Int

Definition Classes
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final def isInstanceOf[T0]: Boolean

Definition Classes
Any
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def next(lastCandidate: DenseVector[Double], lastObservation: Double): DenseVector[Double]

Produces the next candidate, given the last.
Produces the next candidate, given the last. In this case, the next candidate is chosen uniformly from the space.
lastCandidate
the last candidate
lastObservation
the last observed value
returns
the next candidate

Attributes
protected[com.linkedin.photon.ml.hyperparameter.search]
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
def onObservation(point: DenseVector[Double], eval: Double): Unit

Handler callback for each observation.
Handler callback for each observation. In this case, we do nothing.
point
the observed point in the space
eval
the observed value

Attributes
protected[com.linkedin.photon.ml.hyperparameter.search]
def onPriorObservation(point: DenseVector[Double], eval: Double): Unit

Handler callback for each observation in the prior data.
Handler callback for each observation in the prior data. In this case, we do nothing.
point
the observed point in the space
eval
the observed value

Attributes
protected[com.linkedin.photon.ml.hyperparameter.search]
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
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final def wait(): Unit

Definition Classes
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Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

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Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
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Annotations
@throws( ... )

Related Doc: package search

class RandomSearch[T] extends AnyRef

Instance Constructors

new RandomSearch(numParams: Int, evaluationFunction: EvaluationFunction[T], discreteParams: Map[Int, Int] = Map(), kernel: StationaryKernel = new Matern52, seed: Long = System.currentTimeMillis)

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

def discretizeCandidate(candidate: DenseVector[Double], discreteParams: Map[Int, Int]): DenseVector[Double]

def drawCandidates(n: Int): DenseMatrix[Double]

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

def find(n: Int): Seq[T]

def findWithPriorObservations(n: Int, priorObservations: Seq[(DenseVector[Double], Double)]): Seq[T]

def findWithPriors(n: Int, observations: Seq[(DenseVector[Double], Double)], priorObservations: Seq[(DenseVector[Double], Double)]): Seq[T]

final def getClass(): Class[_]

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

def next(lastCandidate: DenseVector[Double], lastObservation: Double): DenseVector[Double]

final def notify(): Unit

final def notifyAll(): Unit

def onObservation(point: DenseVector[Double], eval: Double): Unit

def onPriorObservation(point: DenseVector[Double], eval: Double): Unit

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

def toString(): String

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from AnyRef

Inherited from Any

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