Class/Object

org.apache.spark.ml.recommendation

ALS

Related Docs: object ALS | package recommendation

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class ALS extends Estimator[ALSModel] with ALSParams with DefaultParamsWritable

Alternating Least Squares (ALS) matrix factorization.

ALS attempts to estimate the ratings matrix R as the product of two lower-rank matrices, X and Y, i.e. X * Yt = R. Typically these approximations are called 'factor' matrices. The general approach is iterative. During each iteration, one of the factor matrices is held constant, while the other is solved for using least squares. The newly-solved factor matrix is then held constant while solving for the other factor matrix.

This is a blocked implementation of the ALS factorization algorithm that groups the two sets of factors (referred to as "users" and "products") into blocks and reduces communication by only sending one copy of each user vector to each product block on each iteration, and only for the product blocks that need that user's feature vector. This is achieved by pre-computing some information about the ratings matrix to determine the "out-links" of each user (which blocks of products it will contribute to) and "in-link" information for each product (which of the feature vectors it receives from each user block it will depend on). This allows us to send only an array of feature vectors between each user block and product block, and have the product block find the users' ratings and update the products based on these messages.

For implicit preference data, the algorithm used is based on "Collaborative Filtering for Implicit Feedback Datasets", available at http://dx.doi.org/10.1109/ICDM.2008.22, adapted for the blocked approach used here.

Essentially instead of finding the low-rank approximations to the rating matrix R, this finds the approximations for a preference matrix P where the elements of P are 1 if r is greater than 0 and 0 if r is less than or equal to 0. The ratings then act as 'confidence' values related to strength of indicated user preferences rather than explicit ratings given to items.

Annotations
@Since( "1.3.0" )
Source
ALS.scala
Linear Supertypes
DefaultParamsWritable, MLWritable, ALSParams, HasSeed, HasCheckpointInterval, HasRegParam, HasMaxIter, ALSModelParams, HasPredictionCol, Estimator[ALSModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. ALS
  2. DefaultParamsWritable
  3. MLWritable
  4. ALSParams
  5. HasSeed
  6. HasCheckpointInterval
  7. HasRegParam
  8. HasMaxIter
  9. ALSModelParams
  10. HasPredictionCol
  11. Estimator
  12. PipelineStage
  13. Logging
  14. Params
  15. Serializable
  16. Serializable
  17. Identifiable
  18. AnyRef
  19. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new ALS()

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    Annotations
    @Since( "1.4.0" )
  2. new ALS(uid: String)

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Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T

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    An alias for getOrDefault().

    An alias for getOrDefault().

    Attributes
    protected
    Definition Classes
    Params
  4. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  5. val alpha: DoubleParam

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    Param for the alpha parameter in the implicit preference formulation (nonnegative).

    Param for the alpha parameter in the implicit preference formulation (nonnegative). Default: 1.0

    Definition Classes
    ALSParams
  6. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  7. val checkedCast: UserDefinedFunction

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    Attempts to safely cast a user/item id to an Int.

    Attempts to safely cast a user/item id to an Int. Throws an exception if the value is out of integer range or contains a fractional part.

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

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    Param for set checkpoint interval (>= 1) or disable checkpoint (-1).

    Param for set checkpoint interval (>= 1) or disable checkpoint (-1). E.g. 10 means that the cache will get checkpointed every 10 iterations.

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

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    Clears the user-supplied value for the input param.

    Clears the user-supplied value for the input param.

    Definition Classes
    Params
  10. def clone(): AnyRef

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

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    Param for strategy for dealing with unknown or new users/items at prediction time.

    Param for strategy for dealing with unknown or new users/items at prediction time. This may be useful in cross-validation or production scenarios, for handling user/item ids the model has not seen in the training data. Supported values: - "nan": predicted value for unknown ids will be NaN. - "drop": rows in the input DataFrame containing unknown ids will be dropped from the output DataFrame containing predictions. Default: "nan".

    Definition Classes
    ALSModelParams
  12. def copy(extra: ParamMap): ALS

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    Creates a copy of this instance with the same UID and some extra params.

    Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See defaultCopy().

    Definition Classes
    ALSEstimatorPipelineStageParams
    Annotations
    @Since( "1.5.0" )
  13. def copyValues[T <: Params](to: T, extra: ParamMap = ParamMap.empty): T

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    Copies param values from this instance to another instance for params shared by them.

    Copies param values from this instance to another instance for params shared by them.

    This handles default Params and explicitly set Params separately. Default Params are copied from and to defaultParamMap, and explicitly set Params are copied from and to paramMap. Warning: This implicitly assumes that this Params instance and the target instance share the same set of default Params.

    to

    the target instance, which should work with the same set of default Params as this source instance

    extra

    extra params to be copied to the target's paramMap

    returns

    the target instance with param values copied

    Attributes
    protected
    Definition Classes
    Params
  14. final def defaultCopy[T <: Params](extra: ParamMap): T

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    Default implementation of copy with extra params.

    Default implementation of copy with extra params. It tries to create a new instance with the same UID. Then it copies the embedded and extra parameters over and returns the new instance.

    Attributes
    protected
    Definition Classes
    Params
  15. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  16. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  17. def explainParam(param: Param[_]): String

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    Explains a param.

    Explains a param.

    param

    input param, must belong to this instance.

    returns

    a string that contains the input param name, doc, and optionally its default value and the user-supplied value

    Definition Classes
    Params
  18. def explainParams(): String

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    Explains all params of this instance.

    Explains all params of this instance. See explainParam().

    Definition Classes
    Params
  19. final def extractParamMap(): ParamMap

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    extractParamMap with no extra values.

    extractParamMap with no extra values.

    Definition Classes
    Params
  20. final def extractParamMap(extra: ParamMap): ParamMap

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    Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.

    Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.

    Definition Classes
    Params
  21. val finalStorageLevel: Param[String]

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    Param for StorageLevel for ALS model factors.

    Param for StorageLevel for ALS model factors. Pass in a string representation of StorageLevel. Default: "MEMORY_AND_DISK".

    Definition Classes
    ALSParams
  22. def finalize(): Unit

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

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    Fits a model to the input data.

    Fits a model to the input data.

    Definition Classes
    ALSEstimator
    Annotations
    @Since( "2.0.0" )
  24. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[ALSModel]

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    Fits multiple models to the input data with multiple sets of parameters.

    Fits multiple models to the input data with multiple sets of parameters. The default implementation uses a for loop on each parameter map. Subclasses could override this to optimize multi-model training.

    dataset

    input dataset

    paramMaps

    An array of parameter maps. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted models, matching the input parameter maps

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

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    Fits a single model to the input data with provided parameter map.

    Fits a single model to the input data with provided parameter map.

    dataset

    input dataset

    paramMap

    Parameter map. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted model

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

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    Fits a single model to the input data with optional parameters.

    Fits a single model to the input data with optional parameters.

    dataset

    input dataset

    firstParamPair

    the first param pair, overrides embedded params

    otherParamPairs

    other param pairs. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted model

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

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    Optionally returns the user-supplied value of a param.

    Optionally returns the user-supplied value of a param.

    Definition Classes
    Params
  28. def getAlpha: Double

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    Definition Classes
    ALSParams
  29. final def getCheckpointInterval: Int

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

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    Definition Classes
    AnyRef → Any
  31. def getColdStartStrategy: String

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

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    Gets the default value of a parameter.

    Gets the default value of a parameter.

    Definition Classes
    Params
  33. def getFinalStorageLevel: String

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    Definition Classes
    ALSParams
  34. def getImplicitPrefs: Boolean

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    Definition Classes
    ALSParams
  35. def getIntermediateStorageLevel: String

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    Definition Classes
    ALSParams
  36. def getItemCol: String

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    Definition Classes
    ALSModelParams
  37. final def getMaxIter: Int

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    Definition Classes
    HasMaxIter
  38. def getNonnegative: Boolean

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    Definition Classes
    ALSParams
  39. def getNumItemBlocks: Int

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    Definition Classes
    ALSParams
  40. def getNumUserBlocks: Int

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

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    Gets the value of a param in the embedded param map or its default value.

    Gets the value of a param in the embedded param map or its default value. Throws an exception if neither is set.

    Definition Classes
    Params
  42. def getParam(paramName: String): Param[Any]

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    Gets a param by its name.

    Gets a param by its name.

    Definition Classes
    Params
  43. final def getPredictionCol: String

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    Definition Classes
    HasPredictionCol
  44. def getRank: Int

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    Definition Classes
    ALSParams
  45. def getRatingCol: String

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    Definition Classes
    ALSParams
  46. final def getRegParam: Double

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    Definition Classes
    HasRegParam
  47. final def getSeed: Long

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    Definition Classes
    HasSeed
  48. def getUserCol: String

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    Definition Classes
    ALSModelParams
  49. final def hasDefault[T](param: Param[T]): Boolean

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    Tests whether the input param has a default value set.

    Tests whether the input param has a default value set.

    Definition Classes
    Params
  50. def hasParam(paramName: String): Boolean

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    Tests whether this instance contains a param with a given name.

    Tests whether this instance contains a param with a given name.

    Definition Classes
    Params
  51. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  52. val implicitPrefs: BooleanParam

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    Param to decide whether to use implicit preference.

    Param to decide whether to use implicit preference. Default: false

    Definition Classes
    ALSParams
  53. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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

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    Param for StorageLevel for intermediate datasets.

    Param for StorageLevel for intermediate datasets. Pass in a string representation of StorageLevel. Cannot be "NONE". Default: "MEMORY_AND_DISK".

    Definition Classes
    ALSParams
  55. final def isDefined(param: Param[_]): Boolean

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    Checks whether a param is explicitly set or has a default value.

    Checks whether a param is explicitly set or has a default value.

    Definition Classes
    Params
  56. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  57. final def isSet(param: Param[_]): Boolean

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    Checks whether a param is explicitly set.

    Checks whether a param is explicitly set.

    Definition Classes
    Params
  58. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  59. val itemCol: Param[String]

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    Param for the column name for item ids.

    Param for the column name for item ids. Ids must be integers. Other numeric types are supported for this column, but will be cast to integers as long as they fall within the integer value range. Default: "item"

    Definition Classes
    ALSModelParams
  60. def log: Logger

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    Attributes
    protected
    Definition Classes
    Logging
  61. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  62. def logDebug(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  63. def logError(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  64. def logError(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  65. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  66. def logInfo(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  67. def logName: String

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    Attributes
    protected
    Definition Classes
    Logging
  68. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  69. def logTrace(msg: ⇒ String): Unit

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  72. final val maxIter: IntParam

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    Param for maximum number of iterations (>= 0).

    Param for maximum number of iterations (>= 0).

    Definition Classes
    HasMaxIter
  73. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  74. val nonnegative: BooleanParam

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    Param for whether to apply nonnegativity constraints.

    Param for whether to apply nonnegativity constraints. Default: false

    Definition Classes
    ALSParams
  75. final def notify(): Unit

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    Definition Classes
    AnyRef
  76. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  77. val numItemBlocks: IntParam

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    Param for number of item blocks (positive).

    Param for number of item blocks (positive). Default: 10

    Definition Classes
    ALSParams
  78. val numUserBlocks: IntParam

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    Param for number of user blocks (positive).

    Param for number of user blocks (positive). Default: 10

    Definition Classes
    ALSParams
  79. lazy val params: Array[Param[_]]

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    Returns all params sorted by their names.

    Returns all params sorted by their names. The default implementation uses Java reflection to list all public methods that have no arguments and return Param.

    Definition Classes
    Params
    Note

    Developer should not use this method in constructor because we cannot guarantee that this variable gets initialized before other params.

  80. final val predictionCol: Param[String]

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    Param for prediction column name.

    Param for prediction column name.

    Definition Classes
    HasPredictionCol
  81. val rank: IntParam

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    Param for rank of the matrix factorization (positive).

    Param for rank of the matrix factorization (positive). Default: 10

    Definition Classes
    ALSParams
  82. val ratingCol: Param[String]

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    Param for the column name for ratings.

    Param for the column name for ratings. Default: "rating"

    Definition Classes
    ALSParams
  83. final val regParam: DoubleParam

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    Param for regularization parameter (>= 0).

    Param for regularization parameter (>= 0).

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

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    Saves this ML instance to the input path, a shortcut of write.save(path).

    Saves this ML instance to the input path, a shortcut of write.save(path).

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

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    Param for random seed.

    Param for random seed.

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

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    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

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

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    Sets a parameter (by name) in the embedded param map.

    Sets a parameter (by name) in the embedded param map.

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

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    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

    Definition Classes
    Params
  89. def setAlpha(value: Double): ALS.this.type

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    Annotations
    @Since( "1.3.0" )
  90. def setCheckpointInterval(value: Int): ALS.this.type

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    Annotations
    @Since( "1.4.0" )
  91. def setColdStartStrategy(value: String): ALS.this.type

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    Annotations
    @Since( "2.2.0" )
  92. final def setDefault(paramPairs: ParamPair[_]*): ALS.this.type

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    Sets default values for a list of params.

    Sets default values for a list of params.

    Note: Java developers should use the single-parameter setDefault. Annotating this with varargs can cause compilation failures due to a Scala compiler bug. See SPARK-9268.

    paramPairs

    a list of param pairs that specify params and their default values to set respectively. Make sure that the params are initialized before this method gets called.

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

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    Sets a default value for a param.

    Sets a default value for a param.

    param

    param to set the default value. Make sure that this param is initialized before this method gets called.

    value

    the default value

    Attributes
    protected
    Definition Classes
    Params
  94. def setFinalStorageLevel(value: String): ALS.this.type

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    Annotations
    @Since( "2.0.0" )
  95. def setImplicitPrefs(value: Boolean): ALS.this.type

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    Annotations
    @Since( "1.3.0" )
  96. def setIntermediateStorageLevel(value: String): ALS.this.type

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    Annotations
    @Since( "2.0.0" )
  97. def setItemCol(value: String): ALS.this.type

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    Annotations
    @Since( "1.3.0" )
  98. def setMaxIter(value: Int): ALS.this.type

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    Annotations
    @Since( "1.3.0" )
  99. def setNonnegative(value: Boolean): ALS.this.type

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    Annotations
    @Since( "1.3.0" )
  100. def setNumBlocks(value: Int): ALS.this.type

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    Sets both numUserBlocks and numItemBlocks to the specific value.

    Sets both numUserBlocks and numItemBlocks to the specific value.

    Annotations
    @Since( "1.3.0" )
  101. def setNumItemBlocks(value: Int): ALS.this.type

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    Annotations
    @Since( "1.3.0" )
  102. def setNumUserBlocks(value: Int): ALS.this.type

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    Annotations
    @Since( "1.3.0" )
  103. def setPredictionCol(value: String): ALS.this.type

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    Annotations
    @Since( "1.3.0" )
  104. def setRank(value: Int): ALS.this.type

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    Annotations
    @Since( "1.3.0" )
  105. def setRatingCol(value: String): ALS.this.type

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    Annotations
    @Since( "1.3.0" )
  106. def setRegParam(value: Double): ALS.this.type

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    Annotations
    @Since( "1.3.0" )
  107. def setSeed(value: Long): ALS.this.type

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    Annotations
    @Since( "1.3.0" )
  108. def setUserCol(value: String): ALS.this.type

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    Annotations
    @Since( "1.3.0" )
  109. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  110. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any
  111. def transformSchema(schema: StructType): StructType

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    :: DeveloperApi ::

    :: DeveloperApi ::

    Check transform validity and derive the output schema from the input schema.

    We check validity for interactions between parameters during transformSchema and raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled by Param.validate().

    Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.

    Definition Classes
    ALSPipelineStage
    Annotations
    @Since( "1.3.0" )
  112. def transformSchema(schema: StructType, logging: Boolean): StructType

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    :: DeveloperApi ::

    :: DeveloperApi ::

    Derives the output schema from the input schema and parameters, optionally with logging.

    This should be optimistic. If it is unclear whether the schema will be valid, then it should be assumed valid until proven otherwise.

    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  113. val uid: String

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    An immutable unique ID for the object and its derivatives.

    An immutable unique ID for the object and its derivatives.

    Definition Classes
    ALSIdentifiable
    Annotations
    @Since( "1.4.0" )
  114. val userCol: Param[String]

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    Param for the column name for user ids.

    Param for the column name for user ids. Ids must be integers. Other numeric types are supported for this column, but will be cast to integers as long as they fall within the integer value range. Default: "user"

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

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    Validates and transforms the input schema.

    Validates and transforms the input schema.

    schema

    input schema

    returns

    output schema

    Attributes
    protected
    Definition Classes
    ALSParams
  116. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  117. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  118. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  119. def write: MLWriter

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    Returns an MLWriter instance for this ML instance.

    Returns an MLWriter instance for this ML instance.

    Definition Classes
    DefaultParamsWritableMLWritable

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from ALSParams

Inherited from HasSeed

Inherited from HasCheckpointInterval

Inherited from HasRegParam

Inherited from HasMaxIter

Inherited from ALSModelParams

Inherited from HasPredictionCol

Inherited from Estimator[ALSModel]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Parameters

A list of (hyper-)parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters, respectively.

Members

Parameter setters

Parameter getters

(expert-only) Parameters

A list of advanced, expert-only (hyper-)parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters, respectively.

(expert-only) Parameter setters

(expert-only) Parameter getters