Spark 3.5.5 ScalaDoc - org.apache.spark.ml.recommendation.ALSModel (original) (raw)
class ALSModel extends Model[ALSModel] with ALSModelParams with MLWritable
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Value Members
- final def !=(arg0: Any): Boolean
- final def ##(): Int
- final def $[T](param: Param[T]): T
- final def ==(arg0: Any): Boolean
- final def asInstanceOf[T0]: T0
- final val blockSize: IntParam
- def checkIntegers(dataset: Dataset[_], colName: String): Column
- final def clear(param: Param[_]): ALSModel.this.type
- def clone(): AnyRef
- val coldStartStrategy: Param[String]
- def copy(extra: ParamMap): ALSModel
- def copyValues[T <: Params](to: T, extra: ParamMap = ParamMap.empty): T
- final def defaultCopy[T <: Params](extra: ParamMap): T
- final def eq(arg0: AnyRef): Boolean
- def equals(arg0: Any): Boolean
- def explainParam(param: Param[_]): String
- def explainParams(): String
- final def extractParamMap(): ParamMap
- final def extractParamMap(extra: ParamMap): ParamMap
- def finalize(): Unit
- final def get[T](param: Param[T]): Option[T]
- final def getBlockSize: Int
- final def getClass(): Class[_]
- def getColdStartStrategy: String
- final def getDefault[T](param: Param[T]): Option[T]
- def getItemCol: String
- final def getOrDefault[T](param: Param[T]): T
- def getParam(paramName: String): Param[Any]
- final def getPredictionCol: String
- def getUserCol: String
- final def hasDefault[T](param: Param[T]): Boolean
- def hasParam(paramName: String): Boolean
- def hasParent: Boolean
- def hashCode(): Int
- def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
- def initializeLogIfNecessary(isInterpreter: Boolean): Unit
- final def isDefined(param: Param[_]): Boolean
- final def isInstanceOf[T0]: Boolean
- final def isSet(param: Param[_]): Boolean
- def isTraceEnabled(): Boolean
- val itemCol: Param[String]
- val itemFactors: DataFrame
- def log: Logger
- def logDebug(msg: ⇒ String, throwable: Throwable): Unit
- def logDebug(msg: ⇒ String): Unit
- def logError(msg: ⇒ String, throwable: Throwable): Unit
- def logError(msg: ⇒ String): Unit
- def logInfo(msg: ⇒ String, throwable: Throwable): Unit
- def logInfo(msg: ⇒ String): Unit
- def logName: String
- def logTrace(msg: ⇒ String, throwable: Throwable): Unit
- def logTrace(msg: ⇒ String): Unit
- def logWarning(msg: ⇒ String, throwable: Throwable): Unit
- def logWarning(msg: ⇒ String): Unit
- final def ne(arg0: AnyRef): Boolean
- final def notify(): Unit
- final def notifyAll(): Unit
- lazy val params: Array[Param[_]]
- var parent: Estimator[ALSModel]
- final val predictionCol: Param[String]
- val rank: Int
- def recommendForAllItems(numUsers: Int): DataFrame
- def recommendForAllUsers(numItems: Int): DataFrame
- def recommendForItemSubset(dataset: Dataset[_], numUsers: Int): DataFrame
- def recommendForUserSubset(dataset: Dataset[_], numItems: Int): DataFrame
- def save(path: String): Unit
- final def set(paramPair: ParamPair[_]): ALSModel.this.type
- final def set(param: String, value: Any): ALSModel.this.type
- final def set[T](param: Param[T], value: T): ALSModel.this.type
- def setBlockSize(value: Int): ALSModel.this.type
- def setColdStartStrategy(value: String): ALSModel.this.type
- final def setDefault(paramPairs: ParamPair[_]*): ALSModel.this.type
- final def setDefault[T](param: Param[T], value: T): ALSModel.this.type
- def setItemCol(value: String): ALSModel.this.type
- def setParent(parent: Estimator[ALSModel]): ALSModel
- def setPredictionCol(value: String): ALSModel.this.type
- def setUserCol(value: String): ALSModel.this.type
- final def synchronized[T0](arg0: ⇒ T0): T0
- def toString(): String
- def transform(dataset: Dataset[_]): DataFrame
- def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
- def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
- def transformSchema(schema: StructType): StructType
- def transformSchema(schema: StructType, logging: Boolean): StructType
- val uid: String
- val userCol: Param[String]
- val userFactors: DataFrame
- final def wait(): Unit
- final def wait(arg0: Long, arg1: Int): Unit
- final def wait(arg0: Long): Unit
- def write: MLWriter