abstract class BaseRegressor[F, R <: Regressor[F, R, M], M <: RegressionModel[F, M]] extends Regressor[F, R, M]
Temporary hack to expose private Regressor class in SparkML as a developer API
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- BaseRegressor
- Regressor
- Predictor
- PredictorParams
- HasPredictionCol
- HasFeaturesCol
- HasLabelCol
- Estimator
- PipelineStage
- Logging
- Params
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Instance Constructors
- new BaseRegressor()
Abstract Value Members
Concrete Value Members
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final
def
!=(arg0: Any): Boolean
- Definition Classes
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final
def
##(): Int
- Definition Classes
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final
def
$[T](param: Param[T]): T
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final
def
==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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final
def
clear(param: Param[_]): BaseRegressor.this.type
- Definition Classes
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def
clone(): AnyRef
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- protected[lang]
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def
copyValues[T <: Params](to: T, extra: ParamMap): T
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final
def
defaultCopy[T <: Params](extra: ParamMap): T
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
explainParam(param: Param[_]): String
- Definition Classes
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def
explainParams(): String
- Definition Classes
- Params
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def
extractInstances(dataset: Dataset[_], validateInstance: (Instance) ⇒ Unit): RDD[Instance]
- Attributes
- protected
- Definition Classes
- PredictorParams
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def
extractInstances(dataset: Dataset[_]): RDD[Instance]
- Attributes
- protected
- Definition Classes
- PredictorParams
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def
extractLabeledPoints(dataset: Dataset[_]): RDD[LabeledPoint]
- Attributes
- protected
- Definition Classes
- Predictor
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final
def
extractParamMap(): ParamMap
- Definition Classes
- Params
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final
def
extractParamMap(extra: ParamMap): ParamMap
- Definition Classes
- Params
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final
val
featuresCol: Param[String]
- Definition Classes
- HasFeaturesCol
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def
finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
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- @throws( classOf[java.lang.Throwable] )
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def
fit(dataset: Dataset[_]): M
- Definition Classes
- Predictor → Estimator
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def
fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[M]
- Definition Classes
- Estimator
- Annotations
- @Since( "2.0.0" )
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def
fit(dataset: Dataset[_], paramMap: ParamMap): M
- Definition Classes
- Estimator
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- @Since( "2.0.0" )
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def
fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): M
- Definition Classes
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- @Since( "2.0.0" ) @varargs()
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final
def
get[T](param: Param[T]): Option[T]
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final
def
getClass(): Class[_]
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final
def
getDefault[T](param: Param[T]): Option[T]
- Definition Classes
- Params
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final
def
getFeaturesCol: String
- Definition Classes
- HasFeaturesCol
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final
def
getLabelCol: String
- Definition Classes
- HasLabelCol
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final
def
getOrDefault[T](param: Param[T]): T
- Definition Classes
- Params
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def
getParam(paramName: String): Param[Any]
- Definition Classes
- Params
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final
def
getPredictionCol: String
- Definition Classes
- HasPredictionCol
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final
def
hasDefault[T](param: Param[T]): Boolean
- Definition Classes
- Params
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def
hasParam(paramName: String): Boolean
- Definition Classes
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def
hashCode(): Int
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def
initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
- Attributes
- protected
- Definition Classes
- Logging
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def
initializeLogIfNecessary(isInterpreter: Boolean): Unit
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- protected
- Definition Classes
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final
def
isDefined(param: Param[_]): Boolean
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final
def
isInstanceOf[T0]: Boolean
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final
def
isSet(param: Param[_]): Boolean
- Definition Classes
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def
isTraceEnabled(): Boolean
- Attributes
- protected
- Definition Classes
- Logging
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final
val
labelCol: Param[String]
- Definition Classes
- HasLabelCol
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def
log: Logger
- Attributes
- protected
- Definition Classes
- Logging
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def
logDebug(msg: ⇒ String, throwable: Throwable): Unit
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- protected
- Definition Classes
- Logging
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def
logDebug(msg: ⇒ String): Unit
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- Definition Classes
- Logging
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def
logError(msg: ⇒ String, throwable: Throwable): Unit
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- protected
- Definition Classes
- Logging
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def
logError(msg: ⇒ String): Unit
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- Definition Classes
- Logging
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def
logInfo(msg: ⇒ String, throwable: Throwable): Unit
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- protected
- Definition Classes
- Logging
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def
logInfo(msg: ⇒ String): Unit
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- protected
- Definition Classes
- Logging
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def
logName: String
- Attributes
- protected
- Definition Classes
- Logging
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def
logTrace(msg: ⇒ String, throwable: Throwable): Unit
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- protected
- Definition Classes
- Logging
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def
logTrace(msg: ⇒ String): Unit
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- protected
- Definition Classes
- Logging
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def
logWarning(msg: ⇒ String, throwable: Throwable): Unit
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- protected
- Definition Classes
- Logging
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def
logWarning(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
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final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
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final
def
notify(): Unit
- Definition Classes
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final
def
notifyAll(): Unit
- Definition Classes
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- @native()
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lazy val
params: Array[Param[_]]
- Definition Classes
- Params
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final
val
predictionCol: Param[String]
- Definition Classes
- HasPredictionCol
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final
def
set(paramPair: ParamPair[_]): BaseRegressor.this.type
- Attributes
- protected
- Definition Classes
- Params
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final
def
set(param: String, value: Any): BaseRegressor.this.type
- Attributes
- protected
- Definition Classes
- Params
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final
def
set[T](param: Param[T], value: T): BaseRegressor.this.type
- Definition Classes
- Params
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final
def
setDefault(paramPairs: ParamPair[_]*): BaseRegressor.this.type
- Attributes
- protected
- Definition Classes
- Params
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final
def
setDefault[T](param: Param[T], value: T): BaseRegressor.this.type
- Attributes
- protected
- Definition Classes
- Params
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def
setFeaturesCol(value: String): R
- Definition Classes
- Predictor
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def
setLabelCol(value: String): R
- Definition Classes
- Predictor
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def
setPredictionCol(value: String): R
- Definition Classes
- Predictor
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final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
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def
toString(): String
- Definition Classes
- Identifiable → AnyRef → Any
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def
transformSchema(schema: StructType): StructType
- Definition Classes
- Predictor → PipelineStage
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def
transformSchema(schema: StructType, logging: Boolean): StructType
- Attributes
- protected
- Definition Classes
- PipelineStage
- Annotations
- @DeveloperApi()
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def
validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
- Attributes
- protected
- Definition Classes
- PredictorParams
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final
def
wait(): Unit
- Definition Classes
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- @throws( ... )
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final
def
wait(arg0: Long, arg1: Int): Unit
- Definition Classes
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- @throws( ... )
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final
def
wait(arg0: Long): Unit
- Definition Classes
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