TuneHyperparameters

Instance Constructors

new TuneHyperparameters()
new TuneHyperparameters(uid: String)

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def $[T](param: Param[T]): T

Attributes
protected
Definition Classes
Params
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def BooleanParam(i: Identifiable, name: String, description: String, default: Boolean): BooleanParam

Definition Classes
Wrappable
def BooleanParam(i: Identifiable, name: String, description: String): BooleanParam

Definition Classes
Wrappable
def DoubleParam(i: Identifiable, name: String, description: String, default: Double): DoubleParam

Definition Classes
Wrappable
def DoubleParam(i: Identifiable, name: String, description: String): DoubleParam

Definition Classes
Wrappable
def IntParam(i: Identifiable, name: String, description: String, validation: (Int) ⇒ Boolean): IntParam

Definition Classes
Wrappable
def IntParam(i: Identifiable, name: String, description: String, default: Int): IntParam

Definition Classes
Wrappable
def IntParam(i: Identifiable, name: String, description: String): IntParam

Definition Classes
Wrappable
def LongParam(i: Identifiable, name: String, description: String, default: Long): LongParam

Definition Classes
Wrappable
def LongParam(i: Identifiable, name: String, description: String): LongParam

Definition Classes
Wrappable
def StringParam(i: Identifiable, name: String, description: String, default: String, domain: Seq[String]): Param[String]

Definition Classes
Wrappable
def StringParam(i: Identifiable, name: String, description: String, default: String): Param[String]

Definition Classes
Wrappable
def StringParam(i: Identifiable, name: String, description: String, validation: (String) ⇒ Boolean): Param[String]

Definition Classes
Wrappable
def StringParam(i: Identifiable, name: String, description: String): Param[String]

Definition Classes
Wrappable
final def asInstanceOf[T0]: T0

Definition Classes
Any
def chainedUid(origin: String): String

Definition Classes
Wrappable
final def clear(param: Param[_]): TuneHyperparameters.this.type

Definition Classes
Params
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
def copy(extra: ParamMap): Estimator[TuneHyperparametersModel]

Definition Classes
TuneHyperparameters → Estimator → PipelineStage → Params
def copyValues[T <: Params](to: T, extra: ParamMap): T

Attributes
protected
Definition Classes
Params
final def defaultCopy[T <: Params](extra: ParamMap): T

Attributes
protected
Definition Classes
Params
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
val evaluationMetric: Param[String]

Definition Classes
HasEvaluationMetric
def explainParam(param: Param[_]): String

Definition Classes
Params
def explainParams(): String

Definition Classes
Params
final def extractParamMap(): ParamMap

Definition Classes
Params
final def extractParamMap(extra: ParamMap): ParamMap

Definition Classes
Params
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
def fit(dataset: Dataset[_]): TuneHyperparametersModel

Tunes model hyperparameters for given number of runs and returns the best model found based on evaluation metric.
Tunes model hyperparameters for given number of runs and returns the best model found based on evaluation metric.
dataset
The input dataset to train.
returns
The trained classification model.

Definition Classes
TuneHyperparameters → Estimator
def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[TuneHyperparametersModel]

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
def fit(dataset: Dataset[_], paramMap: ParamMap): TuneHyperparametersModel

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): TuneHyperparametersModel

Definition Classes
Estimator
Annotations
@Since( "2.0.0" ) @varargs()
final def get[T](param: Param[T]): Option[T]

Definition Classes
Params
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
final def getDefault[T](param: Param[T]): Option[T]

Definition Classes
Params
def getEvaluationMetric: String

Definition Classes
HasEvaluationMetric
def getModels: Array[Estimator[_]]
def getNumFolds: Int
def getNumRuns: Int
final def getOrDefault[T](param: Param[T]): T

Definition Classes
Params
def getParallelism: Int
def getParam(paramName: String): Param[Any]

Definition Classes
Params
def getParamSpace: ParamSpace
def getSeed: Long
final def hasDefault[T](param: Param[T]): Boolean

Definition Classes
Params
def hasParam(paramName: String): Boolean

Definition Classes
Params
def hashCode(): Int

Definition Classes
AnyRef → Any
def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

Attributes
protected
Definition Classes
Logging
def initializeLogIfNecessary(isInterpreter: Boolean): Unit

Attributes
protected
Definition Classes
Logging
final def isDefined(param: Param[_]): Boolean

Definition Classes
Params
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
final def isSet(param: Param[_]): Boolean

Definition Classes
Params
def isTraceEnabled(): Boolean

Attributes
protected
Definition Classes
Logging
def log: Logger

Attributes
protected
Definition Classes
Logging
def logDebug(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logDebug(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logError(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logError(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logInfo(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logInfo(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logName: String

Attributes
protected
Definition Classes
Logging
def logTrace(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logTrace(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logWarning(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logWarning(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
val models: EstimatorArrayParam

Estimators to run
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
val numFolds: IntParam
val numRuns: IntParam
val parallelism: IntParam
val paramDomains: Map[String, Seq[String]]

Definition Classes
Wrappable
val paramSpace: ParamSpaceParam
lazy val params: Array[Param[_]]

Definition Classes
Params
def save(path: String): Unit

Definition Classes
MLWritable
Annotations
@Since( "1.6.0" ) @throws( ... )
val seed: LongParam
final def set(paramPair: ParamPair[_]): TuneHyperparameters.this.type

Attributes
protected
Definition Classes
Params
final def set(param: String, value: Any): TuneHyperparameters.this.type

Attributes
protected
Definition Classes
Params
final def set[T](param: Param[T], value: T): TuneHyperparameters.this.type

Definition Classes
Params
final def setDefault(paramPairs: ParamPair[_]*): TuneHyperparameters.this.type

Attributes
protected
Definition Classes
Params
final def setDefault[T](param: Param[T], value: T): TuneHyperparameters.this.type

Attributes
protected
Definition Classes
Params
def setEvaluationMetric(value: String): TuneHyperparameters.this.type

Definition Classes
HasEvaluationMetric
def setModels(value: Array[Estimator[_]]): TuneHyperparameters.this.type
def setNumFolds(value: Int): TuneHyperparameters.this.type
def setNumRuns(value: Int): TuneHyperparameters.this.type
def setParallelism(value: Int): TuneHyperparameters.this.type
def setParamSpace(value: ParamSpace): TuneHyperparameters.this.type
def setSeed(value: Long): TuneHyperparameters.this.type
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
Identifiable → AnyRef → Any
def transformSchema(schema: StructType): StructType

Definition Classes
TuneHyperparameters → PipelineStage
Annotations
@DeveloperApi()
def transformSchema(schema: StructType, logging: Boolean): StructType

Attributes
protected
Definition Classes
PipelineStage
Annotations
@DeveloperApi()
val uid: String

Definition Classes
TuneHyperparameters → Identifiable
final def wait(): Unit

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

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

Definition Classes
AnyRef
Annotations
@throws( ... )
def write: MLWriter

Definition Classes
ComplexParamsWritable → MLWritable

Inherited from HasEvaluationMetric

Inherited from ComplexParamsWritable

Inherited from MLWritable

Inherited from Wrappable

Inherited from Estimator[TuneHyperparametersModel]

Inherited from PipelineStage

Inherited from org.apache.spark.internal.Logging

Inherited from Params

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Parameters

A list of parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters

Parameter setters

Parameter getters

Members

Related Docs: object TuneHyperparameters | package spark

class TuneHyperparameters extends Estimator[TuneHyperparametersModel] with Wrappable with ComplexParamsWritable with HasEvaluationMetric

Instance Constructors

new TuneHyperparameters()

new TuneHyperparameters(uid: String)

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def $[T](param: Param[T]): T

final def ==(arg0: Any): Boolean

def BooleanParam(i: Identifiable, name: String, description: String, default: Boolean): BooleanParam

def BooleanParam(i: Identifiable, name: String, description: String): BooleanParam

def DoubleParam(i: Identifiable, name: String, description: String, default: Double): DoubleParam

def DoubleParam(i: Identifiable, name: String, description: String): DoubleParam

def IntParam(i: Identifiable, name: String, description: String, validation: (Int) ⇒ Boolean): IntParam

def IntParam(i: Identifiable, name: String, description: String, default: Int): IntParam

def IntParam(i: Identifiable, name: String, description: String): IntParam

def LongParam(i: Identifiable, name: String, description: String, default: Long): LongParam

def LongParam(i: Identifiable, name: String, description: String): LongParam

def StringParam(i: Identifiable, name: String, description: String, default: String, domain: Seq[String]): Param[String]

def StringParam(i: Identifiable, name: String, description: String, default: String): Param[String]

def StringParam(i: Identifiable, name: String, description: String, validation: (String) ⇒ Boolean): Param[String]

def StringParam(i: Identifiable, name: String, description: String): Param[String]

final def asInstanceOf[T0]: T0

def chainedUid(origin: String): String

final def clear(param: Param[_]): TuneHyperparameters.this.type

def clone(): AnyRef

def copy(extra: ParamMap): Estimator[TuneHyperparametersModel]

def copyValues[T <: Params](to: T, extra: ParamMap): T

final def defaultCopy[T <: Params](extra: ParamMap): T

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

val evaluationMetric: Param[String]

def explainParam(param: Param[_]): String

def explainParams(): String

final def extractParamMap(): ParamMap

final def extractParamMap(extra: ParamMap): ParamMap

def finalize(): Unit

def fit(dataset: Dataset[_]): TuneHyperparametersModel

def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[TuneHyperparametersModel]

def fit(dataset: Dataset[_], paramMap: ParamMap): TuneHyperparametersModel

def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): TuneHyperparametersModel

final def get[T](param: Param[T]): Option[T]

final def getClass(): Class[_]

final def getDefault[T](param: Param[T]): Option[T]

def getEvaluationMetric: String

def getModels: Array[Estimator[_]]

def getNumFolds: Int

def getNumRuns: Int

final def getOrDefault[T](param: Param[T]): T

def getParallelism: Int

def getParam(paramName: String): Param[Any]

def getParamSpace: ParamSpace

def getSeed: Long

final def hasDefault[T](param: Param[T]): Boolean

def hasParam(paramName: String): Boolean

def hashCode(): Int

def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

final def isDefined(param: Param[_]): Boolean

final def isInstanceOf[T0]: Boolean

final def isSet(param: Param[_]): Boolean

def isTraceEnabled(): Boolean

def log: Logger

def logDebug(msg: ⇒ String, throwable: Throwable): Unit

def logDebug(msg: ⇒ String): Unit

def logError(msg: ⇒ String, throwable: Throwable): Unit

def logError(msg: ⇒ String): Unit

def logInfo(msg: ⇒ String, throwable: Throwable): Unit

def logInfo(msg: ⇒ String): Unit

def logName: String

def logTrace(msg: ⇒ String, throwable: Throwable): Unit

def logTrace(msg: ⇒ String): Unit

def logWarning(msg: ⇒ String, throwable: Throwable): Unit

def logWarning(msg: ⇒ String): Unit

val models: EstimatorArrayParam

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit