org.apache.spark.ml

PipelineModel

class PipelineModel extends Model[PipelineModel] with Logging

:: AlphaComponent :: Represents a compiled pipeline.

Annotations
@AlphaComponent()
Linear Supertypes
Model[PipelineModel], Transformer, Params, Identifiable, PipelineStage, Logging, Serializable, Serializable, AnyRef, Any
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  1. PipelineModel
  2. Model
  3. Transformer
  4. Params
  5. Identifiable
  6. PipelineStage
  7. Logging
  8. Serializable
  9. Serializable
  10. AnyRef
  11. Any
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  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 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. val fittingParamMap: ParamMap

    Fitting parameters, such that parent.

    Fitting parameters, such that parent.fit(..., fittingParamMap) could reproduce the model.

    Definition Classes
    PipelineModelModel
  13. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  14. def getModel[M <: Model[M]](stage: Estimator[M]): M

    Gets the model produced by the input estimator.

    Gets the model produced by the input estimator. Throws an NoSuchElementException is the input estimator does not exist in the pipeline.

  15. def hashCode(): Int

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

    Definition Classes
    Any
  17. def isSet(param: Param[_]): Boolean

    Checks whether a param is explicitly set.

    Checks whether a param is explicitly set.

    Definition Classes
    Params
  18. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging
  19. def log: Logger

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

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

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

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

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

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

    Attributes
    protected
    Definition Classes
    Logging
  26. def logName: String

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

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

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

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

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

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

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

    Definition Classes
    AnyRef
  34. val paramMap: ParamMap

    Internal param map.

    Internal param map.

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

    Returns all params.

    Returns all params.

    Definition Classes
    Params
  36. val parent: Pipeline

    The parent estimator that produced this model.

    The parent estimator that produced this model.

    Definition Classes
    PipelineModelModel
  37. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  38. def toString(): String

    Definition Classes
    AnyRef → Any
  39. def transform(dataset: SchemaRDD, paramMap: ParamMap): SchemaRDD

    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
    PipelineModelTransformer
  40. def transform(dataset: JavaSchemaRDD, paramMap: ParamMap): JavaSchemaRDD

    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
  41. def transform(dataset: JavaSchemaRDD, paramPairs: ParamPair[_]*): JavaSchemaRDD

    Transforms the dataset with optional parameters.

    Transforms the dataset with optional parameters.

    dataset

    input datset

    paramPairs

    optional list of param pairs, overwrite embedded params

    returns

    transformed dataset

    Definition Classes
    Transformer
    Annotations
    @varargs()
  42. def transform(dataset: SchemaRDD, paramPairs: ParamPair[_]*): SchemaRDD

    Transforms the dataset with optional parameters

    Transforms the dataset with optional parameters

    dataset

    input dataset

    paramPairs

    optional list of param pairs, overwrite embedded params

    returns

    transformed dataset

    Definition Classes
    Transformer
    Annotations
    @varargs()
  43. 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
  44. 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
  45. 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
  46. final def wait(): Unit

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

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Model[PipelineModel]

Inherited from Transformer

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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