org.apache.spark.mllib.feature

StandardScaler

class StandardScaler extends Logging

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

Annotations
@Since( "1.1.0" )
Source
StandardScaler.scala
Linear Supertypes
Logging, AnyRef, Any
Ordering
  1. Alphabetic
  2. By inheritance
Inherited
  1. StandardScaler
  2. Logging
  3. AnyRef
  4. Any
  1. Hide All
  2. Show all
Learn more about member selection
Visibility
  1. Public
  2. All

Instance Constructors

  1. new StandardScaler()

    Annotations
    @Since( "1.1.0" )
  2. new StandardScaler(withMean: Boolean, withStd: Boolean)

    withMean

    False by default. Centers the data with mean before scaling. It will build a dense output, so this does not work on sparse input and will raise an exception.

    withStd

    True by default. Scales the data to unit standard deviation.

    Annotations
    @Since( "1.1.0" )

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. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  7. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  9. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  10. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  11. def fit(data: RDD[Vector]): StandardScalerModel

    Computes the mean and variance and stores as a model to be used for later scaling.

    Computes the mean and variance and stores as a model to be used for later scaling.

    data

    The data used to compute the mean and variance to build the transformation model.

    returns

    a StandardScalarModel

    Annotations
    @Since( "1.1.0" )
  12. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  13. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  14. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  15. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging
  16. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging
  17. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  18. def logDebug(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  19. def logError(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  20. def logError(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  21. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  22. def logInfo(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  23. def logName: String

    Attributes
    protected
    Definition Classes
    Logging
  24. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  25. def logTrace(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  26. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  27. def logWarning(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  28. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  29. final def notify(): Unit

    Definition Classes
    AnyRef
  30. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  31. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  32. def toString(): String

    Definition Classes
    AnyRef → Any
  33. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  34. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  35. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Logging

Inherited from AnyRef

Inherited from Any

Ungrouped