Packages

class TrainedClassifierModel extends AutoTrainedModel[TrainedClassifierModel] with Wrappable with SynapseMLLogging

Model produced by TrainClassifier.

Linear Supertypes
SynapseMLLogging, 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. SynapseMLLogging
  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
    SynapseMLLogging
  29. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  30. def logTrain[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  31. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  32. def logVerb[T](verb: String, f: ⇒ T, columns: Int = -1): T
    Definition Classes
    SynapseMLLogging
  33. def makeDotnetFile(conf: CodegenConfig): Unit
    Definition Classes
    DotnetWrappable
  34. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  35. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  36. val model: TransformerParam
    Definition Classes
    AutoTrainedModel
  37. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  38. var parent: Estimator[TrainedClassifierModel]
    Definition Classes
    Model
  39. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  40. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  41. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  42. final def set[T](param: Param[T], value: T): TrainedClassifierModel.this.type
    Definition Classes
    Params
  43. def setFeaturesCol(value: String): TrainedClassifierModel.this.type

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

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