SwUnaryEstimator

Instance Constructors

new SwUnaryEstimator(inputParamName: String, outputParamName: String, operationName: String, sparkMlStageIn: Option[E], uid: String = UID[SwUnaryEstimator[I, O, M, E]])(implicit tti: scala.reflect.api.JavaUniverse.TypeTag[I], tto: scala.reflect.api.JavaUniverse.TypeTag[O], ttov: scala.reflect.api.JavaUniverse.TypeTag[O.Value])

inputParamName
name of spark parameter that sets the second input column
outputParamName
name of spark parameter that sets the first output column
operationName
unique name of the operation this stage performs
sparkMlStageIn
spark estimator to wrap
uid
stage uid
tti
type tag for input
tto
type tag for output
ttov
type tag for output value

Type Members

final type InputFeatures = FeatureLike[I]

Definition Classes
OpPipelineStage1 → OpPipelineStage → InputParams
final type OutputFeatures = FeatureLike[O]

Definition Classes
OpPipelineStage → OpPipelineStageBase

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
final def asInstanceOf[T0]: T0

Definition Classes
Any
final def checkInputLength(features: Array[_]): Boolean

Definition Classes
OpPipelineStage1 → InputParams
def checkSerializable: Try[Unit]

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

Definition Classes
Params
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
final def copy(extra: ParamMap): SwUnaryEstimator.this.type

Definition Classes
OpPipelineStageBase → 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
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[_]): SwUnaryModel[I, O, M]

Definition Classes
SwUnaryEstimator → Estimator
def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[SwUnaryModel[I, O, M]]

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

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

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
final def getInputFeature[T <: FeatureType](i: Int): Option[FeatureLike[T]]

Definition Classes
InputParams
final def getInputFeatures(): Array[OPFeature]

Definition Classes
InputParams
final def getInputSchema(): StructType

Definition Classes
OpPipelineStageParams
final def getMetadata(): Metadata

Definition Classes
OpPipelineStageParams
final def getOrDefault[T](param: Param[T]): T

Definition Classes
Params
def getOutput(): FeatureLike[O]

Definition Classes
OpPipelineStage1 → OpPipelineStageBase
final def getOutputFeatureName: String

Definition Classes
OpPipelineStage
def getParam(paramName: String): Param[Any]

Definition Classes
Params
def getSparkMlStage(): Option[E]

Definition Classes
SparkWrapperParams
def getStageSavePath(): Option[String]

Definition Classes
SparkWrapperParams
final def getTransientFeature(i: Int): Option[TransientFeature]

Definition Classes
InputParams
final def getTransientFeatures(): Array[TransientFeature]

Definition Classes
InputParams
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
final def in1: TransientFeature

Attributes
protected
Definition Classes
HasIn1
def initializeLogIfNecessary(isInterpreter: Boolean): Unit

Attributes
protected
Definition Classes
Logging
final def inputAsArray(in: InputFeatures): Array[OPFeature]

Definition Classes
OpPipelineStage1 → InputParams
val inputParamName: String

name of spark parameter that sets the second input column
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
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
def onGetMetadata(): Unit

Attributes
protected
Definition Classes
OpPipelineStageParams
def onSetInput(): Unit

Attributes
protected
Definition Classes
OpPipelineStageBase
val operationName: String

unique name of the operation this stage performs
unique name of the operation this stage performs

Definition Classes
SwUnaryEstimator → OpPipelineStageBase
final def outputAsArray(out: OutputFeatures): Array[OPFeature]

Definition Classes
OpPipelineStage → OpPipelineStageBase
def outputFeatureUid: String

Attributes
protected[com.salesforce.op]
Definition Classes
OpPipelineStage1 → OpPipelineStage
def outputIsResponse: Boolean

Definition Classes
OpPipelineStage
val outputParamName: String

name of spark parameter that sets the first output column
lazy val params: Array[Param[_]]

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

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

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

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

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

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

Attributes
protected
Definition Classes
Params
final def setInput(features: InputFeatures): SwUnaryEstimator.this.type

Definition Classes
OpPipelineStageBase
final def setInputFeatures[S <: OPFeature](features: Array[S]): SwUnaryEstimator.this.type

Attributes
protected
Definition Classes
InputParams
final def setMetadata(m: Metadata): SwUnaryEstimator.this.type

Definition Classes
OpPipelineStageParams
def setOutputFeatureName(name: String): SwUnaryEstimator.this.type

Definition Classes
OpPipelineStage
def setSparkMlStage(stage: Option[E]): SwUnaryEstimator.this.type

Attributes
protected
Definition Classes
SparkWrapperParams
def setStageSavePath(path: String): SwUnaryEstimator.this.type

Definition Classes
SparkWrapperParams
final val sparkInputColParamNames: StringArrayParam

Definition Classes
SparkWrapperParams
final val sparkMlStage: SparkStageParam[E]

Definition Classes
SparkWrapperParams
final val sparkOutputColParamNames: StringArrayParam

Definition Classes
SparkWrapperParams
final def stageName: String

Definition Classes
OpPipelineStageBase
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

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

Definition Classes
OpPipelineStageBase
def transformSchema(schema: StructType, logging: Boolean): StructType

Attributes
protected
Definition Classes
PipelineStage
Annotations
@DeveloperApi()
implicit val tti: scala.reflect.api.JavaUniverse.TypeTag[I]

type tag for input
implicit val tto: scala.reflect.api.JavaUniverse.TypeTag[O]

type tag for output
type tag for output

Definition Classes
SwUnaryEstimator → OpPipelineStage1
implicit val ttov: scala.reflect.api.JavaUniverse.TypeTag[O.Value]

type tag for output value
type tag for output value

Definition Classes
SwUnaryEstimator → OpPipelineStage1
val uid: String

stage uid
stage uid

Definition Classes
SwUnaryEstimator → 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( ... )
final def write: MLWriter

Definition Classes
OpPipelineStageBase → MLWritable

Related Doc: package generic

class SwUnaryEstimator[I <: FeatureType, O <: FeatureType, M <: Model[M], E <: Estimator[M] with Params] extends Estimator[SwUnaryModel[I, O, M]] with OpPipelineStage1[I, O] with SparkWrapperParams[E]

Instance Constructors

Type Members

final type InputFeatures = FeatureLike[I]

final type OutputFeatures = FeatureLike[O]

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

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

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

final def checkInputLength(features: Array[_]): Boolean

def checkSerializable: Try[Unit]

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

def clone(): AnyRef

final def copy(extra: ParamMap): SwUnaryEstimator.this.type

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

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[_]): SwUnaryModel[I, O, M]

def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[SwUnaryModel[I, O, M]]

def fit(dataset: Dataset[_], paramMap: ParamMap): SwUnaryModel[I, O, M]

def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): SwUnaryModel[I, O, M]

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

final def getClass(): Class[_]

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

final def getInputFeature[T <: FeatureType](i: Int): Option[FeatureLike[T]]

final def getInputFeatures(): Array[OPFeature]

final def getInputSchema(): StructType

final def getMetadata(): Metadata

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

def getOutput(): FeatureLike[O]

final def getOutputFeatureName: String

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

def getSparkMlStage(): Option[E]

def getStageSavePath(): Option[String]

final def getTransientFeature(i: Int): Option[TransientFeature]

final def getTransientFeatures(): Array[TransientFeature]

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

def hasParam(paramName: String): Boolean

def hashCode(): Int

final def in1: TransientFeature

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

final def inputAsArray(in: InputFeatures): Array[OPFeature]

val inputParamName: String

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

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def onGetMetadata(): Unit

def onSetInput(): Unit

val operationName: String

final def outputAsArray(out: OutputFeatures): Array[OPFeature]

def outputFeatureUid: String

def outputIsResponse: Boolean

val outputParamName: String

lazy val params: Array[Param[_]]