trait RankingTrainValidationSplitParams extends Wrappable with HasSeed
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
$[T](param: Param[T]): T
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final
def
==(arg0: Any): Boolean
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def
asInstanceOf[T0]: T0
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lazy val
classNameHelper: String
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final
def
clear(param: Param[_]): RankingTrainValidationSplitParams.this.type
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def
clone(): AnyRef
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def
companionModelClassName: String
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def
copyValues[T <: Params](to: T, extra: ParamMap): T
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lazy val
copyrightLines: String
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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
- Definition Classes
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- val estimator: EstimatorParam
- val estimatorParamMaps: ArrayParamMapParam
- val evaluator: EvaluatorParam
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def
explainParam(param: Param[_]): String
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def
explainParams(): String
- Definition Classes
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final
def
extractParamMap(): ParamMap
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final
def
extractParamMap(extra: ParamMap): ParamMap
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def
finalize(): Unit
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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]
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- def getEstimator: Estimator[_ <: Model[_]]
- def getEstimatorParamMaps: Array[ParamMap]
- def getEvaluator: Evaluator
- def getMinRatingsI: Int
- def getMinRatingsU: Int
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final
def
getOrDefault[T](param: Param[T]): T
- Definition Classes
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def
getParam(paramName: String): Param[Any]
- Definition Classes
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final
def
getSeed: Long
- Definition Classes
- HasSeed
- def getTrainRatio: Double
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final
def
hasDefault[T](param: Param[T]): Boolean
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def
hasParam(paramName: String): Boolean
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def
hashCode(): Int
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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
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def
logTuningParams(instrumentation: Instrumentation): Unit
Instrumentation logging for tuning params including the inner estimator and evaluator info.
Instrumentation logging for tuning params including the inner estimator and evaluator info.
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- protected
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def
makePyFile(conf: CodegenConfig): Unit
- Definition Classes
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def
makeRFile(conf: CodegenConfig): Unit
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- val minRatingsI: IntParam
- val minRatingsU: IntParam
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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lazy val
params: Array[Param[_]]
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def
pyAdditionalMethods: String
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lazy val
pyClassDoc: String
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lazy val
pyClassName: String
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def
pyExtraEstimatorImports: String
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def
pyExtraEstimatorMethods: String
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lazy val
pyInheritedClasses: Seq[String]
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def
pyInitFunc(): String
- Definition Classes
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lazy val
pyInternalWrapper: Boolean
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lazy val
pyObjectBaseClass: String
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def
pyParamArg[T](p: Param[T]): String
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def
pyParamDefault[T](p: Param[T]): Option[String]
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def
pyParamGetter(p: Param[_]): String
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def
pyParamSetter(p: Param[_]): String
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def
pyParamsArgs: String
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def
pyParamsDefaults: String
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lazy val
pyParamsDefinitions: String
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def
pyParamsGetters: String
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def
pyParamsSetters: String
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def
pythonClass(): String
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def
rClass(): String
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def
rDocString: String
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def
rExtraBodyLines: String
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def
rExtraInitLines: String
- Attributes
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lazy val
rFuncName: String
- Attributes
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lazy val
rInternalWrapper: Boolean
- Attributes
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- Definition Classes
- RWrappable
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def
rParamArg[T](p: Param[T]): String
- Attributes
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def
rParamsArgs: String
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def
rSetterLines: String
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final
val
seed: LongParam
- Definition Classes
- HasSeed
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final
def
set(paramPair: ParamPair[_]): RankingTrainValidationSplitParams.this.type
- Attributes
- protected
- Definition Classes
- Params
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final
def
set(param: String, value: Any): RankingTrainValidationSplitParams.this.type
- Attributes
- protected
- Definition Classes
- Params
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final
def
set[T](param: Param[T], value: T): RankingTrainValidationSplitParams.this.type
- Definition Classes
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final
def
setDefault(paramPairs: ParamPair[_]*): RankingTrainValidationSplitParams.this.type
- Attributes
- protected
- Definition Classes
- Params
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final
def
setDefault[T](param: Param[T], value: T): RankingTrainValidationSplitParams.this.type
- Attributes
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final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
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def
toString(): String
- Definition Classes
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val
trainRatio: DoubleParam
Param for ratio between train and validation data.
Param for ratio between train and validation data. Must be between 0 and 1. Default: 0.75
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def
transformSchemaImpl(schema: StructType): StructType
- Attributes
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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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