org.apache.spark.ml.feature

StandardScaler

class StandardScaler extends Estimator[StandardScalerModel] with StandardScalerParams

:: AlphaComponent :: Standardizes features by removing the mean and scaling to unit variance using column summary statistics on the samples in the training set.

Annotations
@AlphaComponent()
Linear Supertypes
StandardScalerParams, HasOutputCol, HasInputCol, Estimator[StandardScalerModel], Params, Identifiable, PipelineStage, Logging, Serializable, Serializable, AnyRef, Any
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  1. StandardScaler
  2. StandardScalerParams
  3. HasOutputCol
  4. HasInputCol
  5. Estimator
  6. Params
  7. Identifiable
  8. PipelineStage
  9. Logging
  10. Serializable
  11. Serializable
  12. AnyRef
  13. Any
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Instance Constructors

  1. new StandardScaler()

Value Members

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

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any

  6. def addOutputColumn(schema: StructType, colName: String, dataType: DataType): StructType

    Attributes
    protected
    Definition Classes
    Params

  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  8. def checkInputColumn(schema: StructType, colName: String, dataType: DataType): Unit

    Check whether the given schema contains an input column.

    Check whether the given schema contains an input column.

    colName

    Parameter name for the input column.

    dataType

    SQL DataType of the input column.

    Attributes
    protected
    Definition Classes
    Params

  9. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  10. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  11. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  12. def explainParams(): String

    Returns the documentation of all params.

    Returns the documentation of all params.

    Definition Classes
    Params

  13. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  14. def fit(dataset: DataFrame, paramMap: ParamMap): StandardScalerModel

    Fits a single model to the input data with provided parameter map.

    Fits a single model to the input data with provided parameter map.

    dataset

    input dataset

    paramMap

    Parameter map. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted model

    Definition Classes
    StandardScaler → Estimator

  15. def fit(dataset: DataFrame, paramMaps: Array[ParamMap]): Seq[StandardScalerModel]

    Fits multiple models to the input data with multiple sets of parameters.

    Fits multiple models to the input data with multiple sets of parameters. The default implementation uses a for loop on each parameter map. Subclasses could overwrite this to optimize multi-model training.

    dataset

    input dataset

    paramMaps

    An array of parameter maps. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted models, matching the input parameter maps

    Definition Classes
    Estimator

  16. def fit(dataset: DataFrame, paramPairs: ParamPair[_]*): StandardScalerModel

    Fits a single model to the input data with optional parameters.

    Fits a single model to the input data with optional parameters.

    dataset

    input dataset

    paramPairs

    Optional list of param pairs. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted model

    Definition Classes
    Estimator
    Annotations
    @varargs()

  17. def get[T](param: Param[T]): T

    Gets the value of a parameter in the embedded param map.

    Gets the value of a parameter in the embedded param map.

    Attributes
    protected
    Definition Classes
    Params

  18. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any

  19. def getInputCol: String

    Definition Classes
    HasInputCol

  20. def getOutputCol: String

    Definition Classes
    HasOutputCol

  21. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  22. val inputCol: Param[String]

    param for input column name

    param for input column name

    Definition Classes
    HasInputCol

  23. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  24. def isSet(param: Param[_]): Boolean

    Checks whether a param is explicitly set.

    Checks whether a param is explicitly set.

    Definition Classes
    Params

  25. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging

  26. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  28. def logDebug(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  30. def logError(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  32. def logInfo(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  33. def logName: String

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  35. def logTrace(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  37. def logWarning(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  38. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  39. final def notify(): Unit

    Definition Classes
    AnyRef

  40. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  41. val outputCol: Param[String]

    param for output column name

    param for output column name

    Definition Classes
    HasOutputCol

  42. val paramMap: ParamMap

    Internal param map.

    Internal param map.

    Attributes
    protected
    Definition Classes
    Params

  43. def params: Array[Param[_]]

    Returns all params.

    Returns all params.

    Definition Classes
    Params

  44. def set[T](param: Param[T], value: T): StandardScaler.this.type

    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

    Attributes
    protected
    Definition Classes
    Params

  45. def setInputCol(value: String): StandardScaler.this.type

  46. def setOutputCol(value: String): StandardScaler.this.type

  47. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef

  48. def toString(): String

    Definition Classes
    AnyRef → Any

  49. def transformSchema(schema: StructType, paramMap: ParamMap): StructType

    :: DeveloperApi ::

    :: DeveloperApi ::

    Derives the output schema from the input schema and parameters. The schema describes the columns and types of the data.

    schema

    Input schema to this stage

    paramMap

    Parameters passed to this stage

    returns

    Output schema from this stage

    Definition Classes
    StandardScaler → PipelineStage

  50. def transformSchema(schema: StructType, paramMap: ParamMap, logging: Boolean): StructType

    Derives the output schema from the input schema and parameters, optionally with logging.

    Derives the output schema from the input schema and parameters, optionally with logging.

    Attributes
    protected
    Definition Classes
    PipelineStage

  51. def validate(): Unit

    Validates parameter values stored internally.

    Validates parameter values stored internally. Raise an exception if any parameter value is invalid.

    Definition Classes
    Params

  52. def validate(paramMap: ParamMap): Unit

    Validates parameter values stored internally plus the input parameter map.

    Validates parameter values stored internally plus the input parameter map. Raises an exception if any parameter is invalid.

    Definition Classes
    Params

  53. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  54. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  55. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from StandardScalerParams

Inherited from HasOutputCol

Inherited from HasInputCol

Inherited from Estimator[StandardScalerModel]

Inherited from Params

Inherited from Identifiable

Inherited from PipelineStage

Inherited from Logging

Inherited from Serializable

Inherited from Serializable

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