c
com.microsoft.azure.synapse.ml.recommendation
RankingTrainValidationSplit
Companion object RankingTrainValidationSplit
class RankingTrainValidationSplit extends Estimator[RankingTrainValidationSplitModel] with RankingTrainValidationSplitParams with Wrappable with ComplexParamsWritable with RecommendationParams with SynapseMLLogging
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Inherited
- RankingTrainValidationSplit
- SynapseMLLogging
- RecommendationParams
- ALSParams
- HasCheckpointInterval
- HasRegParam
- HasMaxIter
- ALSModelParams
- HasBlockSize
- HasPredictionCol
- ComplexParamsWritable
- MLWritable
- RankingTrainValidationSplitParams
- HasSeed
- Wrappable
- DotnetWrappable
- RWrappable
- PythonWrappable
- BaseWrappable
- Estimator
- PipelineStage
- Logging
- Params
- Serializable
- Serializable
- Identifiable
- AnyRef
- Any
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Visibility
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Instance Constructors
Value Members
-
val
alpha: DoubleParam
- Definition Classes
- ALSParams
-
final
val
blockSize: IntParam
- Definition Classes
- HasBlockSize
-
final
val
checkpointInterval: IntParam
- Definition Classes
- HasCheckpointInterval
-
final
def
clear(param: Param[_]): RankingTrainValidationSplit.this.type
- Definition Classes
- Params
-
val
coldStartStrategy: Param[String]
- Definition Classes
- ALSModelParams
-
def
copy(extra: ParamMap): RankingTrainValidationSplit
- Definition Classes
- RankingTrainValidationSplit → Estimator → PipelineStage → Params
-
def
dotnetAdditionalMethods: String
- Definition Classes
- DotnetWrappable
-
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
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val
finalStorageLevel: Param[String]
- Definition Classes
- ALSParams
-
def
fit(dataset: Dataset[_]): RankingTrainValidationSplitModel
- Definition Classes
- RankingTrainValidationSplit → Estimator
-
def
fit(dataset: Dataset[_], paramMaps: Seq[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
getBlockSize: Int
- Definition Classes
- HasBlockSize
-
final
def
getCheckpointInterval: Int
- Definition Classes
- HasCheckpointInterval
-
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
-
def
getParamInfo(p: Param[_]): ParamInfo[_]
- Definition Classes
- BaseWrappable
-
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
-
val
implicitPrefs: BooleanParam
- Definition Classes
- ALSParams
-
val
intermediateStorageLevel: Param[String]
- Definition Classes
- ALSParams
-
final
def
isDefined(param: Param[_]): Boolean
- Definition Classes
- Params
-
final
def
isSet(param: Param[_]): Boolean
- Definition Classes
- Params
-
val
itemCol: Param[String]
- Definition Classes
- ALSModelParams
-
def
logClass(featureName: String): Unit
- Definition Classes
- SynapseMLLogging
-
def
logFit[T](f: ⇒ T, columns: Int): T
- Definition Classes
- SynapseMLLogging
-
def
logTransform[T](f: ⇒ T, columns: Int): T
- Definition Classes
- SynapseMLLogging
-
def
logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
- Definition Classes
- SynapseMLLogging
-
def
makeDotnetFile(conf: CodegenConfig): Unit
- Definition Classes
- DotnetWrappable
-
def
makePyFile(conf: CodegenConfig): Unit
- Definition Classes
- PythonWrappable
-
def
makeRFile(conf: CodegenConfig): Unit
- Definition Classes
- RWrappable
-
final
val
maxIter: IntParam
- Definition Classes
- HasMaxIter
-
val
minRatingsI: IntParam
- Definition Classes
- RankingTrainValidationSplitParams
-
val
minRatingsU: IntParam
- Definition Classes
- RankingTrainValidationSplitParams
-
val
nonnegative: BooleanParam
- Definition Classes
- ALSParams
-
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[_]
-
def
pyAdditionalMethods: String
- Definition Classes
- PythonWrappable
-
def
pyInitFunc(): String
- Definition Classes
- PythonWrappable
-
lazy val
pyInternalWrapper: Boolean
- Definition Classes
- RankingTrainValidationSplit → PythonWrappable
-
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[T](param: Param[T], value: T): RankingTrainValidationSplit.this.type
- Definition Classes
- Params
-
def
setAlpha(value: Double): RankingTrainValidationSplit.this.type
- Definition Classes
- RecommendationParams
-
def
setBlockSize(value: Int): RankingTrainValidationSplit.this.type
- Definition Classes
- RecommendationParams
-
def
setCheckpointInterval(value: Int): RankingTrainValidationSplit.this.type
- Definition Classes
- RecommendationParams
-
def
setColdStartStrategy(value: String): RankingTrainValidationSplit.this.type
- Definition Classes
- RecommendationParams
- def setEstimator(value: Estimator[_ <: Model[_]]): RankingTrainValidationSplit.this.type
- def setEstimatorParamMaps(value: ArrayList[ParamMap]): RankingTrainValidationSplit.this.type
- def setEstimatorParamMaps(value: Array[ParamMap]): RankingTrainValidationSplit.this.type
- def setEvaluator(value: Evaluator): RankingTrainValidationSplit.this.type
-
def
setFinalStorageLevel(value: String): RankingTrainValidationSplit.this.type
- Definition Classes
- RecommendationParams
-
def
setImplicitPrefs(value: Boolean): RankingTrainValidationSplit.this.type
- Definition Classes
- RecommendationParams
-
def
setIntermediateStorageLevel(value: String): RankingTrainValidationSplit.this.type
- Definition Classes
- RecommendationParams
- def setItemCol(value: String): RankingTrainValidationSplit.this.type
-
def
setMaxIter(value: Int): RankingTrainValidationSplit.this.type
- Definition Classes
- RecommendationParams
- def setMinRatingsI(value: Int): RankingTrainValidationSplit.this.type
- def setMinRatingsU(value: Int): RankingTrainValidationSplit.this.type
-
def
setNonnegative(value: Boolean): RankingTrainValidationSplit.this.type
- Definition Classes
- RecommendationParams
-
def
setNumItemBlocks(value: Int): RankingTrainValidationSplit.this.type
- Definition Classes
- RecommendationParams
-
def
setNumUserBlocks(value: Int): RankingTrainValidationSplit.this.type
- Definition Classes
- RecommendationParams
- def setParallelism(value: Int): RankingTrainValidationSplit.this.type
-
def
setPredictionCol(value: String): RankingTrainValidationSplit.this.type
- Definition Classes
- RecommendationParams
-
def
setRank(value: Int): RankingTrainValidationSplit.this.type
- Definition Classes
- RecommendationParams
- def setRatingCol(value: String): RankingTrainValidationSplit.this.type
-
def
setRegParam(value: Double): RankingTrainValidationSplit.this.type
- Definition Classes
- RecommendationParams
-
def
setSeed(value: Long): RankingTrainValidationSplit.this.type
- Definition Classes
- RecommendationParams
- def setTrainRatio(value: Double): RankingTrainValidationSplit.this.type
- def setUserCol(value: String): RankingTrainValidationSplit.this.type
- def splitDF(dataset: DataFrame): Array[DataFrame]
-
def
toString(): String
- Definition Classes
- Identifiable → AnyRef → Any
-
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
- Definition Classes
- RankingTrainValidationSplitParams
-
def
transformSchema(schema: StructType): StructType
- Definition Classes
- RankingTrainValidationSplit → PipelineStage
-
val
uid: String
- Definition Classes
- RankingTrainValidationSplit → SynapseMLLogging → Identifiable
-
val
userCol: Param[String]
- Definition Classes
- ALSModelParams
-
def
write: MLWriter
- Definition Classes
- ComplexParamsWritable → MLWritable