Class/Object

org.apache.spark.ml.feature

Bucketizer

Related Docs: object Bucketizer | package feature

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final class Bucketizer extends Model[Bucketizer] with HasHandleInvalid with HasInputCol with HasOutputCol with HasInputCols with HasOutputCols with DefaultParamsWritable

Bucketizer maps a column of continuous features to a column of feature buckets.

Since 2.3.0, Bucketizer can map multiple columns at once by setting the inputCols parameter. Note that when both the inputCol and inputCols parameters are set, an Exception will be thrown. The splits parameter is only used for single column usage, and splitsArray is for multiple columns.

Annotations
@Since( "1.4.0" )
Source
Bucketizer.scala
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Inherited
  1. Bucketizer
  2. DefaultParamsWritable
  3. MLWritable
  4. HasOutputCols
  5. HasInputCols
  6. HasOutputCol
  7. HasInputCol
  8. HasHandleInvalid
  9. Model
  10. Transformer
  11. PipelineStage
  12. Logging
  13. Params
  14. Serializable
  15. Serializable
  16. Identifiable
  17. AnyRef
  18. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new Bucketizer()

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

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    @Since( "1.4.0" )

Value Members

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

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  2. final def ##(): Int

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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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  5. final def asInstanceOf[T0]: T0

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    Any
  6. final def clear(param: Param[_]): Bucketizer.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
  7. def clone(): AnyRef

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    protected[java.lang]
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    AnyRef
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    @throws( ... )
  8. def copy(extra: ParamMap): Bucketizer

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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
    BucketizerModelTransformerPipelineStageParams
    Annotations
    @Since( "1.4.1" )
  9. 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
  10. 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
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    Params
  11. final def eq(arg0: AnyRef): Boolean

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  12. def equals(arg0: Any): Boolean

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  13. 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
  14. def explainParams(): String

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    Explains all params of this instance.

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

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

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    extractParamMap with no extra values.

    extractParamMap with no extra values.

    Definition Classes
    Params
  16. 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
  17. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  18. 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
  19. final def getClass(): Class[_]

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  20. 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
  21. final def getHandleInvalid: String

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    Definition Classes
    HasHandleInvalid
  22. final def getInputCol: String

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    Definition Classes
    HasInputCol
  23. final def getInputCols: Array[String]

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    Definition Classes
    HasInputCols
  24. 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
  25. final def getOutputCol: String

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    Definition Classes
    HasOutputCol
  26. final def getOutputCols: Array[String]

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    Definition Classes
    HasOutputCols
  27. 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
  28. def getSplits: Array[Double]

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    @Since( "1.4.0" )
  29. def getSplitsArray: Array[Array[Double]]

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    @Since( "2.3.0" )
  30. val handleInvalid: Param[String]

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    Param for how to handle invalid entries.

    Param for how to handle invalid entries. Options are 'skip' (filter out rows with invalid values), 'error' (throw an error), or 'keep' (keep invalid values in a special additional bucket). Note that in the multiple column case, the invalid handling is applied to all columns. That said for 'error' it will throw an error if any invalids are found in any column, for 'skip' it will skip rows with any invalids in any columns, etc. Default: "error"

    Definition Classes
    BucketizerHasHandleInvalid
    Annotations
    @Since( "2.1.0" )
  31. 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
  32. 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
  33. 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
  34. def hashCode(): Int

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  35. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean = false): Boolean

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    Logging
  36. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Logging
  37. final val inputCol: Param[String]

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    Param for input column name.

    Param for input column name.

    Definition Classes
    HasInputCol
  38. final val inputCols: StringArrayParam

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    Param for input column names.

    Param for input column names.

    Definition Classes
    HasInputCols
  39. 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
  40. final def isInstanceOf[T0]: Boolean

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    Any
  41. final def isSet(param: Param[_]): Boolean

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    Checks whether a param is explicitly set.

    Checks whether a param is explicitly set.

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  42. def isTraceEnabled(): Boolean

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    Logging
  43. def log: Logger

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    Logging
  44. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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    Logging
  45. def logDebug(msg: ⇒ String): Unit

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    Logging
  46. def logError(msg: ⇒ String, throwable: Throwable): Unit

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    Logging
  47. def logError(msg: ⇒ String): Unit

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    Logging
  48. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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    Logging
  49. def logInfo(msg: ⇒ String): Unit

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    Logging
  50. def logName: String

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

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

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    Logging
  53. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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

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    Logging
  55. final def ne(arg0: AnyRef): Boolean

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  56. final def notify(): Unit

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  57. final def notifyAll(): Unit

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  58. final val outputCol: Param[String]

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    Param for output column name.

    Param for output column name.

    Definition Classes
    HasOutputCol
  59. final val outputCols: StringArrayParam

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    Param for output column names.

    Param for output column names.

    Definition Classes
    HasOutputCols
  60. 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.

  61. var parent: Estimator[Bucketizer]

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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.

  62. 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( ... )
  63. final def set(paramPair: ParamPair[_]): Bucketizer.this.type

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    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

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    protected
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    Params
  64. final def set(param: String, value: Any): Bucketizer.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
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    Definition Classes
    Params
  65. final def set[T](param: Param[T], value: T): Bucketizer.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
  66. final def setDefault(paramPairs: ParamPair[_]*): Bucketizer.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
  67. final def setDefault[T](param: Param[T], value: T): Bucketizer.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
  68. def setHandleInvalid(value: String): Bucketizer.this.type

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    Annotations
    @Since( "2.1.0" )
  69. def setInputCol(value: String): Bucketizer.this.type

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    @Since( "1.4.0" )
  70. def setInputCols(value: Array[String]): Bucketizer.this.type

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    @Since( "2.3.0" )
  71. def setOutputCol(value: String): Bucketizer.this.type

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    @Since( "1.4.0" )
  72. def setOutputCols(value: Array[String]): Bucketizer.this.type

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    @Since( "2.3.0" )
  73. def setParent(parent: Estimator[Bucketizer]): Bucketizer

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    Sets the parent of this model (Java API).

    Sets the parent of this model (Java API).

    Definition Classes
    Model
  74. def setSplits(value: Array[Double]): Bucketizer.this.type

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    @Since( "1.4.0" )
  75. def setSplitsArray(value: Array[Array[Double]]): Bucketizer.this.type

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    Annotations
    @Since( "2.3.0" )
  76. val splits: DoubleArrayParam

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    Parameter for mapping continuous features into buckets.

    Parameter for mapping continuous features into buckets. With n+1 splits, there are n buckets. A bucket defined by splits x,y holds values in the range [x,y) except the last bucket, which also includes y. Splits should be of length greater than or equal to 3 and strictly increasing. Values at -inf, inf must be explicitly provided to cover all Double values; otherwise, values outside the splits specified will be treated as errors.

    See also handleInvalid, which can optionally create an additional bucket for NaN values.

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    @Since( "1.4.0" )
  77. val splitsArray: DoubleArrayArrayParam

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    Parameter for specifying multiple splits parameters.

    Parameter for specifying multiple splits parameters. Each element in this array can be used to map continuous features into buckets.

    Annotations
    @Since( "2.3.0" )
  78. final def synchronized[T0](arg0: ⇒ T0): T0

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    AnyRef
  79. def toString(): String

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

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    Transforms the input dataset.

    Transforms the input dataset.

    Definition Classes
    BucketizerTransformer
    Annotations
    @Since( "2.0.0" )
  81. 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" )
  82. 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()
  83. 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
    BucketizerPipelineStage
    Annotations
    @Since( "1.4.0" )
  84. 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.

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    PipelineStage
    Annotations
    @DeveloperApi()
  85. 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
    BucketizerIdentifiable
    Annotations
    @Since( "1.4.0" )
  86. final def wait(): Unit

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    @throws( ... )
  87. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  88. final def wait(arg0: Long): Unit

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    @throws( ... )
  89. 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
    BucketizerDefaultParamsWritableMLWritable

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from HasOutputCols

Inherited from HasInputCols

Inherited from HasOutputCol

Inherited from HasInputCol

Inherited from HasHandleInvalid

Inherited from Model[Bucketizer]

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