class SARModel extends Model[SARModel] with BaseRecommendationModel with Wrappable with SARParams with ComplexParamsWritable with SynapseMLLogging
SAR Model
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- By Inheritance
- SARModel
- SynapseMLLogging
- ComplexParamsWritable
- MLWritable
- SARParams
- RecommendationParams
- ALSParams
- HasSeed
- HasCheckpointInterval
- HasRegParam
- HasMaxIter
- Wrappable
- RWrappable
- PythonWrappable
- BaseWrappable
- BaseRecommendationModel
- ALSModelParams
- HasBlockSize
- HasPredictionCol
- Model
- Transformer
- PipelineStage
- Logging
- Params
- Serializable
- Serializable
- Identifiable
- AnyRef
- Any
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Value Members
-
val
activityTimeFormat: Param[String]
- Definition Classes
- SARParams
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val
alpha: DoubleParam
- Definition Classes
- ALSParams
-
final
val
blockSize: IntParam
- Definition Classes
- HasBlockSize
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final
val
checkpointInterval: IntParam
- Definition Classes
- HasCheckpointInterval
-
final
def
clear(param: Param[_]): SARModel.this.type
- Definition Classes
- Params
-
val
coldStartStrategy: Param[String]
- Definition Classes
- ALSModelParams
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def
copy(extra: ParamMap): SARModel
- Definition Classes
- SARModel → Model → Transformer → PipelineStage → Params
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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
-
val
finalStorageLevel: Param[String]
- Definition Classes
- ALSParams
-
final
def
get[T](param: Param[T]): Option[T]
- Definition Classes
- Params
-
def
getALSModel(uid: String, rank: Int, userFactors: DataFrame, itemFactors: DataFrame): ALSModel
- Definition Classes
- BaseRecommendationModel
-
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
getFinalStorageLevel: String
- Definition Classes
- ALSParams
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def
getImplicitPrefs: Boolean
- Definition Classes
- ALSParams
-
def
getIntermediateStorageLevel: String
- Definition Classes
- ALSParams
-
def
getItemCol: String
- Definition Classes
- ALSModelParams
- def getItemDataFrame: DataFrame
-
final
def
getMaxIter: Int
- Definition Classes
- HasMaxIter
-
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
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
getUserCol: String
- Definition Classes
- ALSModelParams
- def getUserDataFrame: DataFrame
-
final
def
hasDefault[T](param: Param[T]): Boolean
- Definition Classes
- Params
-
def
hasParam(paramName: String): Boolean
- Definition Classes
- Params
-
def
hasParent: Boolean
- Definition Classes
- Model
-
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
- val itemDataFrame: DataFrameParam
-
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
makePyFile(conf: CodegenConfig): Unit
- Definition Classes
- PythonWrappable
-
def
makeRFile(conf: CodegenConfig): Unit
- Definition Classes
- RWrappable
-
final
val
maxIter: IntParam
- Definition Classes
- HasMaxIter
-
val
nonnegative: BooleanParam
- Definition Classes
- ALSParams
-
val
numItemBlocks: IntParam
- Definition Classes
- ALSParams
-
val
numUserBlocks: IntParam
- Definition Classes
- ALSParams
-
lazy val
params: Array[Param[_]]
- Definition Classes
- Params
-
var
parent: Estimator[SARModel]
- Definition Classes
- Model
-
final
val
predictionCol: Param[String]
- Definition Classes
- HasPredictionCol
-
def
pyAdditionalMethods: String
- Definition Classes
- PythonWrappable
-
def
pyInitFunc(): String
- Definition Classes
- PythonWrappable
-
val
rank: IntParam
- Definition Classes
- ALSParams
-
val
ratingCol: Param[String]
- Definition Classes
- ALSParams
-
def
recommendForAllItems(numItems: Int): DataFrame
- Definition Classes
- SARModel → BaseRecommendationModel
-
def
recommendForAllUsers(numItems: Int): DataFrame
Returns top
numItems
items recommended for each user, for all users.Returns top
numItems
items recommended for each user, for all users.- numItems
max number of recommendations for each user
- returns
a DataFrame of (userCol: Int, recommendations), where recommendations are stored as an array of (itemCol: Int, rating: Float) Rows.
- Definition Classes
- SARModel → BaseRecommendationModel
-
def
recommendForUserSubset(dataset: Dataset[_], numItems: Int): DataFrame
Returns top
numItems
items recommended for each user id in the input data set.Returns top
numItems
items recommended for each user id in the input data set. Note that if there are duplicate ids in the input dataset, only one set of recommendations per unique id will be returned.- dataset
a Dataset containing a column of user ids. The column name must match
userCol
.- numItems
max number of recommendations for each user.
- returns
a DataFrame of (userCol: Int, recommendations), where recommendations are stored as an array of (itemCol: Int, rating: Float) Rows.
-
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): SARModel.this.type
- Definition Classes
- Params
-
def
setActivityTimeFormat(value: String): SARModel.this.type
- Definition Classes
- SARParams
-
def
setAlpha(value: Double): SARModel.this.type
- Definition Classes
- RecommendationParams
-
def
setBlockSize(value: Int): SARModel.this.type
- Definition Classes
- RecommendationParams
-
def
setCheckpointInterval(value: Int): SARModel.this.type
- Definition Classes
- RecommendationParams
-
def
setColdStartStrategy(value: String): SARModel.this.type
- Definition Classes
- RecommendationParams
-
def
setFinalStorageLevel(value: String): SARModel.this.type
- Definition Classes
- RecommendationParams
-
def
setImplicitPrefs(value: Boolean): SARModel.this.type
- Definition Classes
- RecommendationParams
-
def
setIntermediateStorageLevel(value: String): SARModel.this.type
- Definition Classes
- RecommendationParams
-
def
setItemCol(value: String): SARModel.this.type
- Definition Classes
- SARParams
- def setItemDataFrame(value: DataFrame): SARModel.this.type
-
def
setMaxIter(value: Int): SARModel.this.type
- Definition Classes
- RecommendationParams
-
def
setNonnegative(value: Boolean): SARModel.this.type
- Definition Classes
- RecommendationParams
-
def
setNumItemBlocks(value: Int): SARModel.this.type
- Definition Classes
- RecommendationParams
-
def
setNumUserBlocks(value: Int): SARModel.this.type
- Definition Classes
- RecommendationParams
-
def
setParent(parent: Estimator[SARModel]): SARModel
- Definition Classes
- Model
-
def
setPredictionCol(value: String): SARModel.this.type
- Definition Classes
- RecommendationParams
-
def
setRank(value: Int): SARModel.this.type
- Definition Classes
- RecommendationParams
-
def
setRatingCol(value: String): SARModel.this.type
- Definition Classes
- SARParams
-
def
setRegParam(value: Double): SARModel.this.type
- Definition Classes
- RecommendationParams
-
def
setSeed(value: Long): SARModel.this.type
- Definition Classes
- RecommendationParams
-
def
setSimilarityFunction(value: String): SARModel.this.type
- Definition Classes
- SARParams
-
def
setStartTime(value: String): SARModel.this.type
- Definition Classes
- SARParams
-
def
setStartTimeFormat(value: String): SARModel.this.type
- Definition Classes
- SARParams
-
def
setSupportThreshold(value: Int): SARModel.this.type
- Definition Classes
- SARParams
-
def
setTimeCol(value: String): SARModel.this.type
- Definition Classes
- SARParams
-
def
setTimeDecayCoeff(value: Int): SARModel.this.type
- Definition Classes
- SARParams
-
def
setUserCol(value: String): SARModel.this.type
- Definition Classes
- SARParams
- def setUserDataFrame(value: DataFrame): SARModel.this.type
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val
similarityFunction: Param[String]
- Definition Classes
- SARParams
-
val
startTime: Param[String]
- Definition Classes
- SARParams
-
val
startTimeFormat: Param[String]
- Definition Classes
- SARParams
-
val
supportThreshold: IntParam
- Definition Classes
- SARParams
-
val
timeCol: Param[String]
- Definition Classes
- SARParams
-
val
timeDecayCoeff: IntParam
- Definition Classes
- SARParams
-
def
toString(): String
- Definition Classes
- Identifiable → AnyRef → Any
-
def
transform(dataset: Dataset[_]): DataFrame
- Definition Classes
- SARModel → Transformer
-
def
transform(rank: Int, userDataFrame: DataFrame, itemDataFrame: DataFrame, dataset: Dataset[_]): DataFrame
- Definition Classes
- BaseRecommendationModel
-
def
transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
- Definition Classes
- Transformer
- Annotations
- @Since( "2.0.0" )
-
def
transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
- Definition Classes
- Transformer
- Annotations
- @Since( "2.0.0" ) @varargs()
-
def
transformSchema(schema: StructType): StructType
- Definition Classes
- SARModel → PipelineStage
-
val
uid: String
- Definition Classes
- SARModel → SynapseMLLogging → Identifiable
-
val
userCol: Param[String]
- Definition Classes
- ALSModelParams
- val userDataFrame: DataFrameParam
-
def
write: MLWriter
- Definition Classes
- ComplexParamsWritable → MLWritable