Spark 3.5.5 ScalaDoc - org.apache.spark.ml.Pipeline (original) (raw)

class Pipeline extends Estimator[PipelineModel] with MLWritable

Ordering

  1. Grouped
  2. Alphabetic
  3. By Inheritance

Inherited

  1. Pipeline

  2. MLWritable

  3. Estimator

  4. PipelineStage

  5. Logging

  6. Params

  7. Serializable

  8. Serializable

  9. Identifiable

  10. AnyRef

  11. Any

  12. Hide All

  13. Show All

Instance Constructors

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

Value Members

  1. final def !=(arg0: Any): Boolean
  2. final def ##(): Int
  3. final def $[T](param: Param[T]): T
  4. final def ==(arg0: Any): Boolean
  5. final def asInstanceOf[T0]: T0
  6. final def clear(param: Param[_]): Pipeline.this.type
  7. def clone(): AnyRef
  8. def copy(extra: ParamMap): Pipeline
  9. def copyValues[T <: Params](to: T, extra: ParamMap = ParamMap.empty): T
  10. final def defaultCopy[T <: Params](extra: ParamMap): T
  11. final def eq(arg0: AnyRef): Boolean
  12. def equals(arg0: Any): Boolean
  13. def explainParam(param: Param[_]): String
  14. def explainParams(): String
  15. final def extractParamMap(): ParamMap
  16. final def extractParamMap(extra: ParamMap): ParamMap
  17. def finalize(): Unit
  18. def fit(dataset: Dataset[_]): PipelineModel
  19. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[PipelineModel]
  20. def fit(dataset: Dataset[_], paramMap: ParamMap): PipelineModel
  21. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): PipelineModel
  22. final def get[T](param: Param[T]): Option[T]
  23. final def getClass(): Class[_]
  24. final def getDefault[T](param: Param[T]): Option[T]
  25. final def getOrDefault[T](param: Param[T]): T
  26. def getParam(paramName: String): Param[Any]
  27. def getStages: Array[PipelineStage]
  28. final def hasDefault[T](param: Param[T]): Boolean
  29. def hasParam(paramName: String): Boolean
  30. def hashCode(): Int
  31. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
  32. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
  33. final def isDefined(param: Param[_]): Boolean
  34. final def isInstanceOf[T0]: Boolean
  35. final def isSet(param: Param[_]): Boolean
  36. def isTraceEnabled(): Boolean
  37. def log: Logger
  38. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
  39. def logDebug(msg: ⇒ String): Unit
  40. def logError(msg: ⇒ String, throwable: Throwable): Unit
  41. def logError(msg: ⇒ String): Unit
  42. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
  43. def logInfo(msg: ⇒ String): Unit
  44. def logName: String
  45. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
  46. def logTrace(msg: ⇒ String): Unit
  47. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
  48. def logWarning(msg: ⇒ String): Unit
  49. final def ne(arg0: AnyRef): Boolean
  50. final def notify(): Unit
  51. final def notifyAll(): Unit
  52. lazy val params: Array[Param[_]]
  53. def save(path: String): Unit
  54. final def set(paramPair: ParamPair[_]): Pipeline.this.type
  55. final def set(param: String, value: Any): Pipeline.this.type
  56. final def set[T](param: Param[T], value: T): Pipeline.this.type
  57. final def setDefault(paramPairs: ParamPair[_]*): Pipeline.this.type
  58. final def setDefault[T](param: Param[T], value: T): Pipeline.this.type
  59. def setStages(value: Array[_ <: PipelineStage]): Pipeline.this.type
  60. val stages: Param[Array[PipelineStage]]
  61. final def synchronized[T0](arg0: ⇒ T0): T0
  62. def toString(): String
  63. def transformSchema(schema: StructType): StructType
  64. def transformSchema(schema: StructType, logging: Boolean): StructType
  65. val uid: String
  66. final def wait(): Unit
  67. final def wait(arg0: Long, arg1: Int): Unit
  68. final def wait(arg0: Long): Unit
  69. def write: MLWriter

Parameters

Members

Parameter setters

Parameter getters