class RecursivePipelineModel extends Model[RecursivePipelineModel] with MLWritable with Logging
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def
asInstanceOf[T0]: T0
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def
clear(param: Param[_]): RecursivePipelineModel.this.type
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def
clone(): AnyRef
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def
copy(extra: ParamMap): RecursivePipelineModel
- Definition Classes
- RecursivePipelineModel → Model → Transformer → PipelineStage → Params
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def
copyValues[T <: Params](to: T, extra: ParamMap): T
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def
defaultCopy[T <: Params](extra: ParamMap): T
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explainParam(param: Param[_]): String
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def
explainParams(): String
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def
extractParamMap(): ParamMap
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def
extractParamMap(extra: ParamMap): ParamMap
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finalize(): Unit
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getDefault[T](param: Param[T]): Option[T]
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getOrDefault[T](param: Param[T]): T
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getParam(paramName: String): Param[Any]
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hasParam(paramName: String): Boolean
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hasParent: Boolean
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hashCode(): Int
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def
initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
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def
initializeLogIfNecessary(isInterpreter: Boolean): Unit
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isSet(param: Param[_]): Boolean
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def
isTraceEnabled(): Boolean
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def
log: Logger
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def
logDebug(msg: ⇒ String, throwable: Throwable): Unit
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def
logDebug(msg: ⇒ String): Unit
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def
logError(msg: ⇒ String, throwable: Throwable): Unit
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def
logError(msg: ⇒ String): Unit
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def
logInfo(msg: ⇒ String, throwable: Throwable): Unit
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logInfo(msg: ⇒ String): Unit
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logName: String
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def
logTrace(msg: ⇒ String, throwable: Throwable): Unit
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def
logTrace(msg: ⇒ String): Unit
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def
logWarning(msg: ⇒ String, throwable: Throwable): Unit
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def
logWarning(msg: ⇒ String): Unit
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ne(arg0: AnyRef): Boolean
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def
notify(): Unit
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def
notifyAll(): Unit
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lazy val
params: Array[Param[_]]
- Definition Classes
- Params
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var
parent: Estimator[RecursivePipelineModel]
- Definition Classes
- Model
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def
save(path: String): Unit
- Definition Classes
- MLWritable
- Annotations
- @Since( "1.6.0" ) @throws( ... )
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final
def
set(paramPair: ParamPair[_]): RecursivePipelineModel.this.type
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final
def
set(param: String, value: Any): RecursivePipelineModel.this.type
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final
def
set[T](param: Param[T], value: T): RecursivePipelineModel.this.type
- Definition Classes
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final
def
setDefault(paramPairs: ParamPair[_]*): RecursivePipelineModel.this.type
- Attributes
- protected
- Definition Classes
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final
def
setDefault[T](param: Param[T], value: T): RecursivePipelineModel.this.type
- Attributes
- protected[org.apache.spark.ml]
- Definition Classes
- Params
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def
setParent(parent: Estimator[RecursivePipelineModel]): RecursivePipelineModel
- Definition Classes
- Model
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final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
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def
toString(): String
- Definition Classes
- Identifiable → AnyRef → Any
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def
transform(dataset: Dataset[_]): DataFrame
- Definition Classes
- RecursivePipelineModel → Transformer
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def
transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
- Definition Classes
- Transformer
- Annotations
- @Since( "2.0.0" )
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def
transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
- Definition Classes
- Transformer
- Annotations
- @Since( "2.0.0" ) @varargs()
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def
transformSchema(schema: StructType): StructType
- Definition Classes
- RecursivePipelineModel → PipelineStage
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def
transformSchema(schema: StructType, logging: Boolean): StructType
- Attributes
- protected
- Definition Classes
- PipelineStage
- Annotations
- @DeveloperApi()
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val
uid: String
- Definition Classes
- RecursivePipelineModel → Identifiable
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
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def
write: MLWriter
- Definition Classes
- RecursivePipelineModel → MLWritable