Packages

class ValueIndexer extends Estimator[ValueIndexerModel] with ValueIndexerParams with BasicLogging

Fits a dictionary of values from the input column. Model then transforms a column to a categorical column of the given array of values. Similar to StringIndexer except it can be used on any value types.

Linear Supertypes
BasicLogging, ValueIndexerParams, HasOutputCol, HasInputCol, DefaultParamsWritable, MLWritable, Wrappable, RWrappable, PythonWrappable, BaseWrappable, Estimator[ValueIndexerModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. ValueIndexer
  2. BasicLogging
  3. ValueIndexerParams
  4. HasOutputCol
  5. HasInputCol
  6. DefaultParamsWritable
  7. MLWritable
  8. Wrappable
  9. RWrappable
  10. PythonWrappable
  11. BaseWrappable
  12. Estimator
  13. PipelineStage
  14. Logging
  15. Params
  16. Serializable
  17. Serializable
  18. Identifiable
  19. AnyRef
  20. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new ValueIndexer()
  2. new ValueIndexer(uid: String)

Value Members

  1. final def clear(param: Param[_]): ValueIndexer.this.type
    Definition Classes
    Params
  2. def copy(extra: ParamMap): Estimator[ValueIndexerModel]
    Definition Classes
    ValueIndexer → Estimator → PipelineStage → Params
  3. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  4. def explainParams(): String
    Definition Classes
    Params
  5. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  6. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  7. def fit(dataset: Dataset[_]): ValueIndexerModel

    Fits the dictionary of values from the input column.

    Fits the dictionary of values from the input column.

    dataset

    The input dataset to train.

    returns

    The model for transforming columns to categorical.

    Definition Classes
    ValueIndexer → Estimator
  8. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[ValueIndexerModel]
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  9. def fit(dataset: Dataset[_], paramMap: ParamMap): ValueIndexerModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  10. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): ValueIndexerModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  11. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  12. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  13. def getInputCol: String

    Definition Classes
    HasInputCol
  14. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  15. def getOutputCol: String

    Definition Classes
    HasOutputCol
  16. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  17. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  18. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  19. val inputCol: Param[String]

    The name of the input column

    The name of the input column

    Definition Classes
    HasInputCol
  20. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  21. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  22. def logClass(): Unit
    Definition Classes
    BasicLogging
  23. def logFit[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  24. def logPredict[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  25. def logTrain[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  26. def logTransform[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  27. def logVerb[T](verb: String, f: ⇒ T): T
    Definition Classes
    BasicLogging
  28. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  29. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  30. val outputCol: Param[String]

    The name of the output column

    The name of the output column

    Definition Classes
    HasOutputCol
  31. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  32. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  33. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  34. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  35. final def set[T](param: Param[T], value: T): ValueIndexer.this.type
    Definition Classes
    Params
  36. def setInputCol(value: String): ValueIndexer.this.type

    Definition Classes
    HasInputCol
  37. def setOutputCol(value: String): ValueIndexer.this.type

    Definition Classes
    HasOutputCol
  38. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  39. def transformSchema(schema: StructType): StructType
    Definition Classes
    ValueIndexer → PipelineStage
    Annotations
    @DeveloperApi()
  40. val uid: String
    Definition Classes
    ValueIndexer → BasicLogging → Identifiable
  41. val ver: String
    Definition Classes
    BasicLogging
  42. def write: MLWriter
    Definition Classes
    DefaultParamsWritable → MLWritable