Packages

final class VectorSlicer extends Transformer with HasInputCol with HasOutputCol with DefaultParamsWritable

This class takes a feature vector and outputs a new feature vector with a subarray of the original features.

The subset of features can be specified with either indices (setIndices()) or names (setNames()). At least one feature must be selected. Duplicate features are not allowed, so there can be no overlap between selected indices and names.

The output vector will order features with the selected indices first (in the order given), followed by the selected names (in the order given).

Annotations
@Since( "1.5.0" )
Source
VectorSlicer.scala
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  1. VectorSlicer
  2. DefaultParamsWritable
  3. MLWritable
  4. HasOutputCol
  5. HasInputCol
  6. Transformer
  7. PipelineStage
  8. Logging
  9. Params
  10. Serializable
  11. Serializable
  12. Identifiable
  13. AnyRef
  14. 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 indices: IntArrayParam

    An array of indices to select features from a vector column.

    An array of indices to select features from a vector column. There can be no overlap with names. Default: Empty array

    Annotations
    @Since( "1.5.0" )
  2. final val inputCol: Param[String]

    Param for input column name.

    Param for input column name.

    Definition Classes
    HasInputCol
  3. val names: StringArrayParam

    An array of feature names to select features from a vector column.

    An array of feature names to select features from a vector column. These names must be specified by ML org.apache.spark.ml.attribute.Attributes. There can be no overlap with indices. Default: Empty Array

    Annotations
    @Since( "1.5.0" )
  4. final val outputCol: Param[String]

    Param for output column name.

    Param for output column name.

    Definition Classes
    HasOutputCol

Members

  1. final def clear(param: Param[_]): VectorSlicer.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): VectorSlicer

    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
    VectorSlicerTransformerPipelineStageParams
    Annotations
    @Since( "1.5.0" )
  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. 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
  14. final def isSet(param: Param[_]): Boolean

    Checks whether a param is explicitly set.

    Checks whether a param is explicitly set.

    Definition Classes
    Params
  15. 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.

  16. 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( ... )
  17. final def set[T](param: Param[T], value: T): VectorSlicer.this.type

    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

    Definition Classes
    Params
  18. def toString(): String
    Definition Classes
    VectorSlicerIdentifiable → AnyRef → Any
    Annotations
    @Since( "3.0.0" )
  19. def transform(dataset: Dataset[_]): DataFrame

    Transforms the input dataset.

    Transforms the input dataset.

    Definition Classes
    VectorSlicerTransformer
    Annotations
    @Since( "2.0.0" )
  20. 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" )
  21. 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()
  22. 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
    VectorSlicerPipelineStage
    Annotations
    @Since( "1.5.0" )
  23. 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
    VectorSlicerIdentifiable
    Annotations
    @Since( "1.5.0" )
  24. 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 setIndices(value: Array[Int]): VectorSlicer.this.type

    Annotations
    @Since( "1.5.0" )
  2. def setInputCol(value: String): VectorSlicer.this.type

    Annotations
    @Since( "1.5.0" )
  3. def setNames(value: Array[String]): VectorSlicer.this.type

    Annotations
    @Since( "1.5.0" )
  4. def setOutputCol(value: String): VectorSlicer.this.type

    Annotations
    @Since( "1.5.0" )

Parameter getters

  1. def getIndices: Array[Int]

    Annotations
    @Since( "1.5.0" )
  2. final def getInputCol: String

    Definition Classes
    HasInputCol
  3. def getNames: Array[String]

    Annotations
    @Since( "1.5.0" )
  4. final def getOutputCol: String

    Definition Classes
    HasOutputCol