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

Model produced by TuneHyperparameters.

Linear Supertypes
SynapseMLLogging, HasBestModel, Wrappable, 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. RWrappable
  6. PythonWrappable
  7. BaseWrappable
  8. ComplexParamsWritable
  9. MLWritable
  10. Model
  11. Transformer
  12. PipelineStage
  13. Logging
  14. Params
  15. Serializable
  16. Serializable
  17. Identifiable
  18. AnyRef
  19. 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 explainParam(param: Param[_]): String
    Definition Classes
    Params
  6. def explainParams(): String
    Definition Classes
    Params
  7. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  8. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  9. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  10. def getBestMetric: Double
  11. def getBestModel: Transformer

    The best model found during evaluation.

    The best model found during evaluation.

    returns

    The best model.

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