Packages

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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Parameters

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

  1. val handleInvalid: Param[String]

    Param for how to handle invalid entries containing NaN values.

    Param for how to handle invalid entries containing NaN values. Values outside the splits will always be treated as errors. 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" )
  2. final val inputCol: Param[String]

    Param for input column name.

    Param for input column name.

    Definition Classes
    HasInputCol
  3. final val inputCols: StringArrayParam

    Param for input column names.

    Param for input column names.

    Definition Classes
    HasInputCols
  4. final val outputCol: Param[String]

    Param for output column name.

    Param for output column name.

    Definition Classes
    HasOutputCol
  5. final val outputCols: StringArrayParam

    Param for output column names.

    Param for output column names.

    Definition Classes
    HasOutputCols
  6. val splits: DoubleArrayParam

    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.

    Annotations
    @Since( "1.4.0" )
  7. val splitsArray: DoubleArrayArrayParam

    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" )

Members

  1. final def clear(param: Param[_]): Bucketizer.this.type

    Clears the user-supplied value for the input param.

    Clears the user-supplied value for the input param.

    Definition Classes
    Params
  2. def copy(extra: ParamMap): Bucketizer

    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" )
  3. 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
  4. def explainParams(): String

    Explains all params of this instance.

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

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

    extractParamMap with no extra values.

    extractParamMap with no extra values.

    Definition Classes
    Params
  6. 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.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
  7. 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
  8. 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
  9. 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
  10. def getParam(paramName: String): Param[Any]

    Gets a param by its name.

    Gets a param by its name.

    Definition Classes
    Params
  11. 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
  12. 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
  13. def hasParent: Boolean

    Indicates whether this Model has a corresponding parent.

    Indicates whether this Model has a corresponding parent.

    Definition Classes
    Model
  14. 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
  15. final def isSet(param: Param[_]): Boolean

    Checks whether a param is explicitly set.

    Checks whether a param is explicitly set.

    Definition Classes
    Params
  16. 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.

    Definition Classes
    Params
    Note

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

  17. var parent: Estimator[Bucketizer]

    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.

  18. def save(path: String): Unit

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

    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

    Definition Classes
    Params
  20. def setParent(parent: Estimator[Bucketizer]): Bucketizer

    Sets the parent of this model (Java API).

    Sets the parent of this model (Java API).

    Definition Classes
    Model
  21. def toString(): String
    Definition Classes
    BucketizerIdentifiable → AnyRef → Any
    Annotations
    @Since( "3.0.0" )
  22. def transform(dataset: Dataset[_]): DataFrame

    Transforms the input dataset.

    Transforms the input dataset.

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

    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" )
  24. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

    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()
  25. def transformSchema(schema: StructType): StructType

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

    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" )
  26. 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
    BucketizerIdentifiable
    Annotations
    @Since( "1.4.0" )
  27. def write: MLWriter

    Returns an MLWriter instance for this ML instance.

    Returns an MLWriter instance for this ML instance.

    Definition Classes
    DefaultParamsWritableMLWritable

Parameter setters

  1. def setHandleInvalid(value: String): Bucketizer.this.type

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

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

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

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

    Annotations
    @Since( "2.3.0" )
  6. def setSplits(value: Array[Double]): Bucketizer.this.type

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

    Annotations
    @Since( "2.3.0" )

Parameter getters

  1. final def getHandleInvalid: String

    Definition Classes
    HasHandleInvalid
  2. final def getInputCol: String

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

    Definition Classes
    HasInputCols
  4. final def getOutputCol: String

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

    Definition Classes
    HasOutputCols
  6. def getSplits: Array[Double]

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

    Annotations
    @Since( "2.3.0" )