class TuneHyperparametersModel extends Model[TuneHyperparametersModel] with ComplexParamsWritable with Wrappable with HasBestModel with SynapseMLLogging

Model produced by TuneHyperparameters.

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

Instance Constructors

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

Value Members

  1. val bestMetric: DoubleParam
  2. val bestModel: TransformerParam
    Definition Classes
    HasBestModel
  3. final def clear(param: Param[_]): TuneHyperparametersModel.this.type
    Definition Classes
    Params
  4. def copy(extra: ParamMap): TuneHyperparametersModel
    Definition Classes
    TuneHyperparametersModel → Model → Transformer → PipelineStage → Params
  5. def dotnetAdditionalMethods: String
    Definition Classes
    DotnetWrappable
  6. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  7. def explainParams(): String
    Definition Classes
    Params
  8. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  9. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  10. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  11. def getBestMetric: Double
  12. def getBestModel: Transformer

    The best model found during evaluation.

    The best model found during evaluation.

    returns

    The best model.

    Definition Classes
    HasBestModel
  13. def getBestModelInfo: String
  14. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  15. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  16. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  17. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  18. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  19. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  20. def hasParent: Boolean
    Definition Classes
    Model
  21. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  22. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  23. def logClass(): Unit
    Definition Classes
    SynapseMLLogging
  24. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  25. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  26. def logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
    Definition Classes
    SynapseMLLogging
  27. def makeDotnetFile(conf: CodegenConfig): Unit
    Definition Classes
    DotnetWrappable
  28. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  29. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  30. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  31. var parent: Estimator[TuneHyperparametersModel]
    Definition Classes
    Model
  32. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  33. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  34. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  35. final def set[T](param: Param[T], value: T): TuneHyperparametersModel.this.type
    Definition Classes
    Params
  36. def setBestMetric(v: Double): TuneHyperparametersModel.this.type
  37. def setBestModel(v: Transformer): TuneHyperparametersModel.this.type
    Definition Classes
    HasBestModel
  38. def setParent(parent: Estimator[TuneHyperparametersModel]): TuneHyperparametersModel
    Definition Classes
    Model
  39. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  40. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    TuneHyperparametersModel → Transformer
  41. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  42. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  43. def transformSchema(schema: StructType): StructType
    Definition Classes
    TuneHyperparametersModel → PipelineStage
  44. val uid: String
    Definition Classes
    TuneHyperparametersModelSynapseMLLogging → Identifiable
  45. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable