Class/Object

org.apache.spark.ml.recommendation

ALSModel

Related Docs: object ALSModel | package recommendation

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class ALSModel extends Model[ALSModel] with ALSModelParams with MLWritable

Model fitted by ALS.

Annotations
@Since( "1.3.0" )
Source
ALS.scala
Linear Supertypes
MLWritable, ALSModelParams, HasPredictionCol, Model[ALSModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. ALSModel
  2. MLWritable
  3. ALSModelParams
  4. HasPredictionCol
  5. Model
  6. Transformer
  7. PipelineStage
  8. Logging
  9. Params
  10. Serializable
  11. Serializable
  12. Identifiable
  13. AnyRef
  14. Any
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Visibility
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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
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  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. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  6. 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
  7. final def clear(param: Param[_]): ALSModel.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
  8. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  9. 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
  10. def copy(extra: ParamMap): ALSModel

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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
    ALSModelModelTransformerPipelineStageParams
    Annotations
    @Since( "1.5.0" )
  11. 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
  12. 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
  13. final def eq(arg0: AnyRef): Boolean

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

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    Definition Classes
    AnyRef → Any
  15. 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
  16. def explainParams(): String

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    Explains all params of this instance.

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

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

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    extractParamMap with no extra values.

    extractParamMap with no extra values.

    Definition Classes
    Params
  18. 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
  19. def finalize(): Unit

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    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  20. 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
  21. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any
  22. def getColdStartStrategy: String

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    Definition Classes
    ALSModelParams
  23. 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
  24. def getItemCol: String

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    Definition Classes
    ALSModelParams
  25. 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
  26. 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
  27. final def getPredictionCol: String

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    Definition Classes
    HasPredictionCol
  28. def getUserCol: String

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    Definition Classes
    ALSModelParams
  29. 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
  30. 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
  31. def hasParent: Boolean

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    Indicates whether this Model has a corresponding parent.

    Indicates whether this Model has a corresponding parent.

    Definition Classes
    Model
  32. def hashCode(): Int

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    Definition Classes
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  33. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean = false): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  34. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    protected
    Definition Classes
    Logging
  35. 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
  36. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  37. 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
  38. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  39. 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
  40. val itemFactors: DataFrame

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    a DataFrame that stores item factors in two columns: id and features

  41. def log: Logger

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

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    Definition Classes
    Logging
  43. def logDebug(msg: ⇒ String): Unit

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

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    Definition Classes
    Logging
  45. def logError(msg: ⇒ String): Unit

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

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    Definition Classes
    Logging
  47. def logInfo(msg: ⇒ String): Unit

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    Definition Classes
    Logging
  48. def logName: String

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    Logging
  49. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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    Definition Classes
    Logging
  50. def logTrace(msg: ⇒ String): Unit

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

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    Logging
  52. def logWarning(msg: ⇒ String): Unit

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    protected
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    Logging
  53. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  54. final def notify(): Unit

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

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    Definition Classes
    AnyRef
  56. 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.

  57. var parent: Estimator[ALSModel]

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    The parent estimator that produced this model.

    The parent estimator that produced this model.

    Definition Classes
    Model
    Note

    For ensembles' component Models, this value can be null.

  58. final val predictionCol: Param[String]

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    Param for prediction column name.

    Param for prediction column name.

    Definition Classes
    HasPredictionCol
  59. val rank: Int

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    rank of the matrix factorization model

    rank of the matrix factorization model

    Annotations
    @Since( "1.4.0" )
  60. def recommendForAllItems(numUsers: Int): DataFrame

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    Returns top numUsers users recommended for each item, for all items.

    Returns top numUsers users recommended for each item, for all items.

    numUsers

    max number of recommendations for each item

    returns

    a DataFrame of (itemCol: Int, recommendations), where recommendations are stored as an array of (userCol: Int, rating: Float) Rows.

    Annotations
    @Since( "2.2.0" )
  61. def recommendForAllUsers(numItems: Int): DataFrame

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    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.

    Annotations
    @Since( "2.2.0" )
  62. def recommendForItemSubset(dataset: Dataset[_], numUsers: Int): DataFrame

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    Returns top numUsers users recommended for each item id in the input data set.

    Returns top numUsers users recommended for each item 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 item ids. The column name must match itemCol.

    numUsers

    max number of recommendations for each item.

    returns

    a DataFrame of (itemCol: Int, recommendations), where recommendations are stored as an array of (userCol: Int, rating: Float) Rows.

    Annotations
    @Since( "2.3.0" )
  63. def recommendForUserSubset(dataset: Dataset[_], numItems: Int): DataFrame

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    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.

    Annotations
    @Since( "2.3.0" )
  64. 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( ... )
  65. final def set(paramPair: ParamPair[_]): ALSModel.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
  66. final def set(param: String, value: Any): ALSModel.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
  67. final def set[T](param: Param[T], value: T): ALSModel.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
  68. def setColdStartStrategy(value: String): ALSModel.this.type

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    Annotations
    @Since( "2.2.0" )
  69. final def setDefault(paramPairs: ParamPair[_]*): ALSModel.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
  70. final def setDefault[T](param: Param[T], value: T): ALSModel.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
  71. def setItemCol(value: String): ALSModel.this.type

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    Annotations
    @Since( "1.4.0" )
  72. def setParent(parent: Estimator[ALSModel]): ALSModel

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    Sets the parent of this model (Java API).

    Sets the parent of this model (Java API).

    Definition Classes
    Model
  73. def setPredictionCol(value: String): ALSModel.this.type

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    Annotations
    @Since( "1.3.0" )
  74. def setUserCol(value: String): ALSModel.this.type

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    Annotations
    @Since( "1.4.0" )
  75. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  76. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any
  77. def transform(dataset: Dataset[_]): DataFrame

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    Transforms the input dataset.

    Transforms the input dataset.

    Definition Classes
    ALSModelTransformer
    Annotations
    @Since( "2.0.0" )
  78. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

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    Transforms the dataset with provided parameter map as additional parameters.

    Transforms the dataset with provided parameter map as additional parameters.

    dataset

    input dataset

    paramMap

    additional parameters, overwrite embedded params

    returns

    transformed dataset

    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  79. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

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    Transforms the dataset with optional parameters

    Transforms the dataset with optional parameters

    dataset

    input dataset

    firstParamPair

    the first param pair, overwrite embedded params

    otherParamPairs

    other param pairs, overwrite embedded params

    returns

    transformed dataset

    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  80. 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
    ALSModelPipelineStage
    Annotations
    @Since( "1.3.0" )
  81. 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()
  82. 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
    ALSModelIdentifiable
    Annotations
    @Since( "1.4.0" )
  83. 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
  84. val userFactors: DataFrame

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    a DataFrame that stores user factors in two columns: id and features

  85. final def wait(): Unit

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

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  88. 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
    ALSModelMLWritable
    Annotations
    @Since( "1.6.0" )

Inherited from MLWritable

Inherited from ALSModelParams

Inherited from HasPredictionCol

Inherited from Model[ALSModel]

Inherited from Transformer

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