Packages

class TrainedClassifierModel extends AutoTrainedModel[TrainedClassifierModel] with Wrappable with BasicLogging

Model produced by TrainClassifier.

Linear Supertypes
BasicLogging, Wrappable, DotnetWrappable, RWrappable, PythonWrappable, BaseWrappable, AutoTrainedModel[TrainedClassifierModel], HasFeaturesCol, HasLabelCol, ComplexParamsWritable, MLWritable, Model[TrainedClassifierModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. TrainedClassifierModel
  2. BasicLogging
  3. Wrappable
  4. DotnetWrappable
  5. RWrappable
  6. PythonWrappable
  7. BaseWrappable
  8. AutoTrainedModel
  9. HasFeaturesCol
  10. HasLabelCol
  11. ComplexParamsWritable
  12. MLWritable
  13. Model
  14. Transformer
  15. PipelineStage
  16. Logging
  17. Params
  18. Serializable
  19. Serializable
  20. Identifiable
  21. AnyRef
  22. Any
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Visibility
  1. Public
  2. All

Instance Constructors

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

Value Members

  1. final def clear(param: Param[_]): TrainedClassifierModel.this.type
    Definition Classes
    Params
  2. def copy(extra: ParamMap): TrainedClassifierModel
    Definition Classes
    TrainedClassifierModel → Model → Transformer → PipelineStage → Params
  3. def dotnetAdditionalMethods: String
    Definition Classes
    DotnetWrappable
  4. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  5. def explainParams(): String
    Definition Classes
    Params
  6. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  7. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  8. val featuresCol: Param[String]

    The name of the features column

    The name of the features column

    Definition Classes
    HasFeaturesCol
  9. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  10. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  11. def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol
  12. def getLabelCol: String

    Definition Classes
    HasLabelCol
  13. def getLastStage: Transformer

    Retrieve the underlying model.

    Retrieve the underlying model.

    returns

    The underlying model.

    Definition Classes
    AutoTrainedModel
  14. def getLevels: Array[Any]
  15. def getModel: PipelineModel
    Definition Classes
    AutoTrainedModel
  16. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  17. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  18. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  19. def getParamMap: ParamMap

    Retrieve the param map from the underlying model.

    Retrieve the param map from the underlying model.

    returns

    The param map from the underlying model.

    Definition Classes
    AutoTrainedModel
  20. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  21. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  22. def hasParent: Boolean
    Definition Classes
    Model
  23. def hasScoreColumns(model: Transformer): Boolean
  24. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  25. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  26. val labelCol: Param[String]

    The name of the label column

    The name of the label column

    Definition Classes
    HasLabelCol
  27. val levels: UntypedArrayParam
  28. def logClass(): Unit
    Definition Classes
    BasicLogging
  29. def logFit[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  30. def logPredict[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  31. def logTrain[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  32. def logTransform[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  33. def logVerb[T](verb: String, f: ⇒ T): T
    Definition Classes
    BasicLogging
  34. def makeDotnetFile(conf: CodegenConfig): Unit
    Definition Classes
    DotnetWrappable
  35. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  36. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  37. val model: TransformerParam
    Definition Classes
    AutoTrainedModel
  38. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  39. var parent: Estimator[TrainedClassifierModel]
    Definition Classes
    Model
  40. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  41. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  42. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  43. final def set[T](param: Param[T], value: T): TrainedClassifierModel.this.type
    Definition Classes
    Params
  44. def setFeaturesCol(value: String): TrainedClassifierModel.this.type

    Definition Classes
    HasFeaturesCol
  45. def setLabelCol(value: String): TrainedClassifierModel.this.type

    Definition Classes
    HasLabelCol
  46. def setLevels(v: ArrayList[Any]): TrainedClassifierModel.this.type
  47. def setLevels(v: Array[_]): TrainedClassifierModel.this.type
  48. def setModel(v: PipelineModel): TrainedClassifierModel.this.type
    Definition Classes
    AutoTrainedModel
  49. def setParent(parent: Estimator[TrainedClassifierModel]): TrainedClassifierModel
    Definition Classes
    Model
  50. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  51. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    TrainedClassifierModel → Transformer
  52. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  53. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  54. def transformSchema(schema: StructType): StructType
    Definition Classes
    TrainedClassifierModel → PipelineStage
    Annotations
    @DeveloperApi()
  55. val uid: String
    Definition Classes
    TrainedClassifierModel → BasicLogging → Identifiable
  56. val ver: String
    Definition Classes
    BasicLogging
  57. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable