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com.johnsnowlabs.nlp.annotators.param

EvaluationDLParams

trait EvaluationDLParams extends Params

Linear Supertypes
Params, Serializable, Serializable, Identifiable, AnyRef, Any
Known Subclasses
ClassifierDLApproach, ClassifierEncoder, MultiClassifierDLApproach, SentimentDLApproach, NerDLApproach
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Inherited
  1. EvaluationDLParams
  2. Params
  3. Serializable
  4. Serializable
  5. Identifiable
  6. AnyRef
  7. Any
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Visibility
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Abstract Value Members

  1. abstract def copy(extra: ParamMap): Params
    Definition Classes
    Params
  2. abstract val uid: String
    Definition Classes
    Identifiable

Concrete Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. final def clear(param: Param[_]): EvaluationDLParams.this.type
    Definition Classes
    Params
  7. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  8. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  9. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  10. val enableOutputLogs: BooleanParam

    Whether to output to annotators log folder (Default: false)

  11. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  12. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  13. val evaluationLogExtended: BooleanParam

    Whether logs for validation to be extended (Default: false): it displays time and evaluation of each label

  14. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  15. def explainParams(): String
    Definition Classes
    Params
  16. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  17. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  18. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  19. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  20. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  21. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  22. def getEnableOutputLogs: Boolean

    Whether to output to annotators log folder (Default: false)

  23. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  24. def getOutputLogsPath: String

    Folder path to save training logs (Default: "")

  25. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  26. def getValidationSplit: Float

    Choose the proportion of training dataset to be validated against the model on each Epoch (Default: 0.0f).

    Choose the proportion of training dataset to be validated against the model on each Epoch (Default: 0.0f). The value should be between 0.0 and 1.0 and by default it is 0.0 and off.

  27. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  28. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  29. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  30. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  31. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  32. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  33. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  34. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  35. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  36. val outputLogsPath: Param[String]

    Folder path to save training logs (Default: "")

  37. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  38. final def set(paramPair: ParamPair[_]): EvaluationDLParams.this.type
    Attributes
    protected
    Definition Classes
    Params
  39. final def set(param: String, value: Any): EvaluationDLParams.this.type
    Attributes
    protected
    Definition Classes
    Params
  40. final def set[T](param: Param[T], value: T): EvaluationDLParams.this.type
    Definition Classes
    Params
  41. final def setDefault(paramPairs: ParamPair[_]*): EvaluationDLParams.this.type
    Attributes
    protected
    Definition Classes
    Params
  42. final def setDefault[T](param: Param[T], value: T): EvaluationDLParams.this.type
    Attributes
    protected
    Definition Classes
    Params
  43. def setEnableOutputLogs(enableOutputLogs: Boolean): EvaluationDLParams.this.type

    Whether to output to annotators log folder (Default: false)

  44. def setEvaluationLogExtended(evaluationLogExtended: Boolean): EvaluationDLParams.this.type

    Whether logs for validation to be extended: it displays time and evaluation of each label.

    Whether logs for validation to be extended: it displays time and evaluation of each label. Default is false.

  45. def setOutputLogsPath(path: String): EvaluationDLParams.this.type

    Folder path to save training logs (Default: "")

  46. def setTestDataset(er: ExternalResource): EvaluationDLParams.this.type

    Path to test dataset.

    Path to test dataset. If set, it is used to calculate statistics on it during training.

  47. def setTestDataset(path: String, readAs: Format = ReadAs.SPARK, options: Map[String, String] = Map("format" -> "parquet")): EvaluationDLParams.this.type

    Path to test dataset.

    Path to test dataset. If set, it is used to calculate statistics on it during training.

  48. def setValidationSplit(validationSplit: Float): EvaluationDLParams.this.type

    Choose the proportion of training dataset to be validated against the model on each Epoch (Default: 0.0f).

    Choose the proportion of training dataset to be validated against the model on each Epoch (Default: 0.0f). The value should be between 0.0 and 1.0 and by default it is 0.0 and off.

  49. def setVerbose(verbose: Level): EvaluationDLParams.this.type

    Level of verbosity during training (Default: Verbose.Silent.id)

  50. def setVerbose(verbose: Int): EvaluationDLParams.this.type

    Level of verbosity during training (Default: Verbose.Silent.id)

  51. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  52. val testDataset: ExternalResourceParam

    Path to test dataset.

    Path to test dataset. If set, it is used to calculate statistics on it during training.

  53. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  54. val validationSplit: FloatParam

    Choose the proportion of training dataset to be validated against the model on each Epoch (Default: 0.0f).

    Choose the proportion of training dataset to be validated against the model on each Epoch (Default: 0.0f). The value should be between 0.0 and 1.0 and by default it is 0.0 and off.

  55. val verbose: IntParam

    Level of verbosity during training (Default: Verbose.Silent.id)

  56. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  57. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  58. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

getParam

param

setParam

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