org.apache.spark.ml.recommendation

ALS

class ALS extends Estimator[ALSModel] with ALSParams

:: Experimental :: 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 > 0 and 0 if r <= 0. The ratings then act as 'confidence' values related to strength of indicated user preferences rather than explicit ratings given to items.

Annotations
@Experimental()
Linear Supertypes
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. ALSParams
  3. HasSeed
  4. HasCheckpointInterval
  5. HasRegParam
  6. HasMaxIter
  7. ALSModelParams
  8. HasPredictionCol
  9. Estimator
  10. PipelineStage
  11. Logging
  12. Params
  13. Serializable
  14. Serializable
  15. Identifiable
  16. AnyRef
  17. Any
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  1. Public
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Instance Constructors

  1. new ALS()

  2. new ALS(uid: String)

Value Members

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

    Definition Classes
    AnyRef
  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any
  3. final def ##(): Int

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

    An alias for getOrDefault().

    An alias for getOrDefault().

    Attributes
    protected
    Definition Classes
    Params
  5. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  6. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  7. val alpha: DoubleParam

    Param for the alpha parameter in the implicit preference formulation (>= 0).

    Param for the alpha parameter in the implicit preference formulation (>= 0). Default: 1.0

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

    Definition Classes
    Any
  9. final val checkpointInterval: IntParam

    Param for checkpoint interval (>= 1).

    Param for checkpoint interval (>= 1).

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

    Clears the user-supplied value for the input param.

    Clears the user-supplied value for the input param.

    Attributes
    protected
    Definition Classes
    Params
  11. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  12. def copy(extra: ParamMap): ALS

    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.

    Definition Classes
    ALSEstimatorPipelineStageParams
    See also

    defaultCopy()

  13. def copyValues[T <: Params](to: T, extra: ParamMap = ParamMap.empty): T

    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.

    to

    the target instance

    extra

    extra params to be copied

    returns

    the target instance with param values copied

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

    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

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

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

    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

    Explains all params of this instance.

    Explains all params of this instance.

    Definition Classes
    Params
    See also

    explainParam()

  19. final def extractParamMap(): ParamMap

    extractParamMap with no extra values.

    extractParamMap with no extra values.

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

    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.

    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 < user-supplied values < extra.

    Definition Classes
    Params
  21. def finalize(): Unit

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

    Fits a model to the input data.

    Fits a model to the input data.

    Definition Classes
    ALSEstimator
  23. def fit(dataset: DataFrame, paramMaps: Array[ParamMap]): Seq[ALSModel]

    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
  24. def fit(dataset: DataFrame, paramMap: ParamMap): ALSModel

    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
  25. def fit(dataset: DataFrame, firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): ALSModel

    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
    @varargs()
  26. final def get[T](param: Param[T]): Option[T]

    Optionally returns the user-supplied value of a param.

    Optionally returns the user-supplied value of a param.

    Definition Classes
    Params
  27. def getAlpha: Double

    Definition Classes
    ALSParams
  28. final def getCheckpointInterval: Int

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

    Definition Classes
    AnyRef → Any
  30. final def getDefault[T](param: Param[T]): Option[T]

    Gets the default value of a parameter.

    Gets the default value of a parameter.

    Definition Classes
    Params
  31. def getImplicitPrefs: Boolean

    Definition Classes
    ALSParams
  32. def getItemCol: String

    Definition Classes
    ALSModelParams
  33. final def getMaxIter: Int

    Definition Classes
    HasMaxIter
  34. def getNonnegative: Boolean

    Definition Classes
    ALSParams
  35. def getNumItemBlocks: Int

    Definition Classes
    ALSParams
  36. def getNumUserBlocks: Int

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

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

    Gets a param by its name.

    Gets a param by its name.

    Definition Classes
    Params
  39. final def getPredictionCol: String

    Definition Classes
    HasPredictionCol
  40. def getRank: Int

    Definition Classes
    ALSParams
  41. def getRatingCol: String

    Definition Classes
    ALSParams
  42. final def getRegParam: Double

    Definition Classes
    HasRegParam
  43. final def getSeed: Long

    Definition Classes
    HasSeed
  44. def getUserCol: String

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

    Tests whether the input param has a default value set.

    Tests whether the input param has a default value set.

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

    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
  47. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  48. val implicitPrefs: BooleanParam

    Param to decide whether to use implicit preference.

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

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

    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
  50. final def isInstanceOf[T0]: Boolean

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

    Checks whether a param is explicitly set.

    Checks whether a param is explicitly set.

    Definition Classes
    Params
  52. def isTraceEnabled(): Boolean

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

    Param for the column name for item ids.

    Param for the column name for item ids. Default: "item"

    Definition Classes
    ALSModelParams
  54. def log: Logger

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

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

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

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

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

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

    Attributes
    protected
    Definition Classes
    Logging
  61. def logName: String

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

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

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

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

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

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

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

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

    Definition Classes
    AnyRef
  68. val nonnegative: BooleanParam

    Param for whether to apply nonnegativity constraints.

    Param for whether to apply nonnegativity constraints. Default: false

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

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

    Definition Classes
    AnyRef
  71. val numItemBlocks: IntParam

    Param for number of item blocks (>= 1).

    Param for number of item blocks (>= 1). Default: 10

    Definition Classes
    ALSParams
  72. val numUserBlocks: IntParam

    Param for number of user blocks (>= 1).

    Param for number of user blocks (>= 1). Default: 10

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

    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.

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

    Definition Classes
    Params
  74. final val predictionCol: Param[String]

    Param for prediction column name.

    Param for prediction column name.

    Definition Classes
    HasPredictionCol
  75. val rank: IntParam

    Param for rank of the matrix factorization (>= 1).

    Param for rank of the matrix factorization (>= 1). Default: 10

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

    Param for the column name for ratings.

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

    Definition Classes
    ALSParams
  77. final val regParam: DoubleParam

    Param for regularization parameter (>= 0).

    Param for regularization parameter (>= 0).

    Definition Classes
    HasRegParam
  78. final val seed: LongParam

    Param for random seed.

    Param for random seed.

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

    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

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

    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
  81. final def set[T](param: Param[T], value: T): ALS.this.type

    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

    Attributes
    protected
    Definition Classes
    Params
  82. def setAlpha(value: Double): ALS.this.type

  83. def setCheckpointInterval(value: Int): ALS.this.type

  84. final def setDefault(paramPairs: ParamPair[_]*): ALS.this.type

    Sets default values for a list of params.

    Sets default values for a list of params.

    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
    Annotations
    @varargs()
  85. final def setDefault[T](param: Param[T], value: T): ALS.this.type

    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
  86. def setImplicitPrefs(value: Boolean): ALS.this.type

  87. def setItemCol(value: String): ALS.this.type

  88. def setMaxIter(value: Int): ALS.this.type

  89. def setNonnegative(value: Boolean): ALS.this.type

  90. def setNumBlocks(value: Int): ALS.this.type

    Sets both numUserBlocks and numItemBlocks to the specific value.

  91. def setNumItemBlocks(value: Int): ALS.this.type

  92. def setNumUserBlocks(value: Int): ALS.this.type

  93. def setPredictionCol(value: String): ALS.this.type

  94. def setRank(value: Int): ALS.this.type

  95. def setRatingCol(value: String): ALS.this.type

  96. def setRegParam(value: Double): ALS.this.type

  97. def setSeed(value: Long): ALS.this.type

  98. def setUserCol(value: String): ALS.this.type

  99. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  100. def toString(): String

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

    :: DeveloperApi ::

    :: DeveloperApi ::

    Derives the output schema from the input schema.

    Definition Classes
    ALSPipelineStage
  102. def transformSchema(schema: StructType, logging: Boolean): StructType

    :: 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()
  103. val uid: String

    An immutable unique ID for the object and its derivatives.

    An immutable unique ID for the object and its derivatives.

    Definition Classes
    ALS → Identifiable
  104. val userCol: Param[String]

    Param for the column name for user ids.

    Param for the column name for user ids. Default: "user"

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

    Validates and transforms the input schema.

    Validates and transforms the input schema.

    schema

    input schema

    returns

    output schema

    Attributes
    protected
    Definition Classes
    ALSParams
  106. def validateParams(): Unit

    Validates parameter values stored internally.

    Validates parameter values stored internally. Raise an exception if any parameter value is invalid.

    This only needs to check for interactions between parameters. Parameter value checks which do not depend on other parameters are handled by Param.validate(). This method does not handle input/output column parameters; those are checked during schema validation.

    Definition Classes
    Params
  107. final def wait(): Unit

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

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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