RankingTrainValidationSplit

Instance Constructors

new RankingTrainValidationSplit()
new RankingTrainValidationSplit(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
val alpha: DoubleParam

Definition Classes
ALSParams
final def asInstanceOf[T0]: T0

Definition Classes
Any
val checkedCast: UserDefinedFunction

Attributes
protected[org.apache.spark.ml.recommendation]
Definition Classes
ALSModelParams
final val checkpointInterval: IntParam

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

Definition Classes
Params
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
val coldStartStrategy: Param[String]

Definition Classes
ALSModelParams
def copy(extra: ParamMap): RankingTrainValidationSplit

Definition Classes
RankingTrainValidationSplit → 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 estimator: EstimatorParam

Definition Classes
RankingTrainValidationSplitParams
val estimatorParamMaps: ArrayParamMapParam

Definition Classes
RankingTrainValidationSplitParams
val evaluator: EvaluatorParam

Definition Classes
RankingTrainValidationSplitParams
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 filterRatings(dataset: Dataset[_]): DataFrame
val finalStorageLevel: Param[String]

Definition Classes
ALSParams
def finalize(): Unit

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

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

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

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

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

Definition Classes
Params
def getAlpha: Double

Definition Classes
ALSParams
final def getCheckpointInterval: Int

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

Definition Classes
AnyRef → Any
def getColdStartStrategy: String

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

Definition Classes
Params
def getEstimator: Estimator[_ <: Model[_]]

Definition Classes
RankingTrainValidationSplitParams
def getEstimatorParamMaps: Array[ParamMap]

Definition Classes
RankingTrainValidationSplitParams
def getEvaluator: Evaluator

Definition Classes
RankingTrainValidationSplitParams
def getFinalStorageLevel: String

Definition Classes
ALSParams
def getImplicitPrefs: Boolean

Definition Classes
ALSParams
def getIntermediateStorageLevel: String

Definition Classes
ALSParams
def getItemCol: String

Definition Classes
ALSModelParams
final def getMaxIter: Int

Definition Classes
HasMaxIter
def getMinRatingsI: Int

Definition Classes
RankingTrainValidationSplitParams
def getMinRatingsU: Int

Definition Classes
RankingTrainValidationSplitParams
def getNonnegative: Boolean

Definition Classes
ALSParams
def getNumItemBlocks: Int

Definition Classes
ALSParams
def getNumUserBlocks: Int

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

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

Definition Classes
Params
final def getPredictionCol: String

Definition Classes
HasPredictionCol
def getRank: Int

Definition Classes
ALSParams
def getRatingCol: String

Definition Classes
ALSParams
final def getRegParam: Double

Definition Classes
HasRegParam
final def getSeed: Long

Definition Classes
HasSeed
def getTrainRatio: Double

Definition Classes
RankingTrainValidationSplitParams
def getUserCol: String

Definition Classes
ALSModelParams
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
val implicitPrefs: BooleanParam

Definition Classes
ALSParams
def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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

Attributes
protected
Definition Classes
Logging
val intermediateStorageLevel: Param[String]

Definition Classes
ALSParams
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
val itemCol: Param[String]

Definition Classes
ALSModelParams
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 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.

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

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

Attributes
protected
Definition Classes
Logging
final val maxIter: IntParam

Definition Classes
HasMaxIter
val minRatingsI: IntParam

Definition Classes
RankingTrainValidationSplitParams
val minRatingsU: IntParam

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

Definition Classes
RankingTrainValidationSplitParams
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
val nonnegative: BooleanParam

Definition Classes
ALSParams
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
val numItemBlocks: IntParam

Definition Classes
ALSParams
val numUserBlocks: IntParam

Definition Classes
ALSParams
val parallelism: IntParam

The number of threads to use when running parallel algorithms.
The number of threads to use when running parallel algorithms. Default is 1 for serial execution
lazy val params: Array[Param[_]]

Definition Classes
Params
final val predictionCol: Param[String]

Definition Classes
HasPredictionCol
def prepareTestData(validationDataset: DataFrame, recs: DataFrame, k: Int): Dataset[_]
val rank: IntParam

Definition Classes
ALSParams
val ratingCol: Param[String]

Definition Classes
ALSParams
final val regParam: DoubleParam

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

Definition Classes
MLWritable
Annotations
@Since( "1.6.0" ) @throws( ... )
final val seed: LongParam

Definition Classes
HasSeed
final def set(paramPair: ParamPair[_]): RankingTrainValidationSplit.this.type

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

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

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

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

Attributes
protected
Definition Classes
Params
def setEstimator(value: Estimator[_ <: Model[_]]): RankingTrainValidationSplit.this.type
def setEstimatorParamMaps(value: Array[ParamMap]): RankingTrainValidationSplit.this.type
def setEvaluator(value: Evaluator): RankingTrainValidationSplit.this.type
def setItemCol(value: String): RankingTrainValidationSplit.this.type
def setMinRatingsI(value: Int): RankingTrainValidationSplit.this.type
def setMinRatingsU(value: Int): RankingTrainValidationSplit.this.type
def setParallelism(value: Int): RankingTrainValidationSplit.this.type
def setRatingCol(value: String): RankingTrainValidationSplit.this.type
def setSeed(value: Long): RankingTrainValidationSplit.this.type
def setTrainRatio(value: Double): RankingTrainValidationSplit.this.type
def setUserCol(value: String): RankingTrainValidationSplit.this.type
def splitDF(dataset: DataFrame): Array[DataFrame]
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
Identifiable → AnyRef → Any
val trainRatio: DoubleParam

Definition Classes
RankingTrainValidationSplitParams
def transformSchema(schema: StructType): StructType

Definition Classes
RankingTrainValidationSplit → PipelineStage
def transformSchema(schema: StructType, logging: Boolean): StructType

Attributes
protected
Definition Classes
PipelineStage
Annotations
@DeveloperApi()
def transformSchemaImpl(schema: StructType): StructType

Attributes
protected
Definition Classes
RankingTrainValidationSplitParams
val uid: String

Definition Classes
RankingTrainValidationSplit → Identifiable
val userCol: Param[String]

Definition Classes
ALSModelParams
def validateAndTransformSchema(schema: StructType): StructType

Attributes
protected
Definition Classes
ALSParams
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 RecommendationParams

Inherited from ALSParams

Inherited from HasCheckpointInterval

Inherited from HasRegParam

Inherited from HasMaxIter

Inherited from ALSModelParams

Inherited from HasPredictionCol

Inherited from ComplexParamsWritable

Inherited from MLWritable

Inherited from RankingTrainValidationSplitParams

Inherited from HasSeed

Inherited from Wrappable

Inherited from Estimator[RankingTrainValidationSplitModel]

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

expertGetParam

expertParam

expertSetParam

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 RankingTrainValidationSplit | package spark

class RankingTrainValidationSplit extends Estimator[RankingTrainValidationSplitModel] with RankingTrainValidationSplitParams with Wrappable with ComplexParamsWritable with RecommendationParams

Instance Constructors

new RankingTrainValidationSplit()

new RankingTrainValidationSplit(uid: String)

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

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

final def ==(arg0: Any): Boolean

val alpha: DoubleParam

final def asInstanceOf[T0]: T0

val checkedCast: UserDefinedFunction

final val checkpointInterval: IntParam

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

def clone(): AnyRef

val coldStartStrategy: Param[String]

def copy(extra: ParamMap): RankingTrainValidationSplit

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 estimator: EstimatorParam

val estimatorParamMaps: ArrayParamMapParam

val evaluator: EvaluatorParam

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

def explainParams(): String

final def extractParamMap(): ParamMap

final def extractParamMap(extra: ParamMap): ParamMap

def filterRatings(dataset: Dataset[_]): DataFrame

val finalStorageLevel: Param[String]

def finalize(): Unit

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

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

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

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

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

def getAlpha: Double

final def getCheckpointInterval: Int

final def getClass(): Class[_]

def getColdStartStrategy: String

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

def getEstimator: Estimator[_ <: Model[_]]

def getEstimatorParamMaps: Array[ParamMap]

def getEvaluator: Evaluator

def getFinalStorageLevel: String

def getImplicitPrefs: Boolean

def getIntermediateStorageLevel: String

def getItemCol: String

final def getMaxIter: Int

def getMinRatingsI: Int

def getMinRatingsU: Int

def getNonnegative: Boolean

def getNumItemBlocks: Int

def getNumUserBlocks: Int

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

def getParallelism: Int

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

final def getPredictionCol: String

def getRank: Int

def getRatingCol: String

final def getRegParam: Double

final def getSeed: Long

def getTrainRatio: Double

def getUserCol: String

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

def hasParam(paramName: String): Boolean

def hashCode(): Int

val implicitPrefs: BooleanParam

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

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

val intermediateStorageLevel: Param[String]

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

final def isInstanceOf[T0]: Boolean

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

def isTraceEnabled(): Boolean

val itemCol: Param[String]

def log: Logger

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