org.apache.spark.ml

Estimator

abstract class Estimator[M <: Model[M]] extends PipelineStage with Params

:: AlphaComponent :: Abstract class for estimators that fit models to data.

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@AlphaComponent()
Linear Supertypes
Params, Identifiable, PipelineStage, Logging, Serializable, Serializable, AnyRef, Any
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  1. Estimator
  2. Params
  3. Identifiable
  4. PipelineStage
  5. Logging
  6. Serializable
  7. Serializable
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Instance Constructors

  1. new Estimator()

Abstract Value Members

  1. abstract def fit(dataset: SchemaRDD, paramMap: ParamMap): M

    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

    returns

    fitted model

Concrete Value Members

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

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

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  3. final def ##(): Int

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

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

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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

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  9. def equals(arg0: Any): Boolean

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  10. def explainParams(): String

    Returns the documentation of all params.

    Returns the documentation of all params.

    Definition Classes
    Params
  11. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  12. def fit(dataset: JavaSchemaRDD, paramMaps: Array[ParamMap]): List[M]

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

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

    dataset

    input dataset

    paramMaps

    an array of parameter maps

    returns

    fitted models, matching the input parameter maps

  13. def fit(dataset: JavaSchemaRDD, paramMap: ParamMap): M

    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

    returns

    fitted model

  14. def fit(dataset: JavaSchemaRDD, paramPairs: ParamPair[_]*): M

    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 (overwrite embedded params)

    returns

    fitted model

    Annotations
    @varargs()
  15. def fit(dataset: SchemaRDD, paramMaps: Array[ParamMap]): Seq[M]

    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

    returns

    fitted models, matching the input parameter maps

  16. def fit(dataset: SchemaRDD, paramPairs: ParamPair[_]*): M

    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 (overwrite embedded params)

    returns

    fitted model

    Annotations
    @varargs()
  17. final def getClass(): Class[_]

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  18. def hashCode(): Int

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  19. final def isInstanceOf[T0]: Boolean

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

    Checks whether a param is explicitly set.

    Checks whether a param is explicitly set.

    Definition Classes
    Params
  21. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging
  22. def log: Logger

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

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    protected
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  24. def logDebug(msg: ⇒ String): Unit

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

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    protected
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  26. def logError(msg: ⇒ String): Unit

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

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

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    protected
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  29. def logName: String

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

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    protected
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    Logging
  31. def logTrace(msg: ⇒ String): Unit

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

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    protected
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  33. def logWarning(msg: ⇒ String): Unit

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    protected
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  34. final def ne(arg0: AnyRef): Boolean

    Definition Classes
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  35. final def notify(): Unit

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

    Definition Classes
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  37. val paramMap: ParamMap

    Internal param map.

    Internal param map.

    Attributes
    protected
    Definition Classes
    Params
  38. def params: Array[Param[_]]

    Returns all params.

    Returns all params.

    Definition Classes
    Params
  39. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  40. def toString(): String

    Definition Classes
    AnyRef → Any
  41. 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
  42. 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
  43. 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
  44. final def wait(): Unit

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    @throws( ... )
  45. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  46. final def wait(arg0: Long): Unit

    Definition Classes
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    @throws( ... )

Inherited from Params

Inherited from Identifiable

Inherited from PipelineStage

Inherited from Logging

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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