org.apache.spark.ml.tuning

TrainValidationSplitModel

class TrainValidationSplitModel extends Model[TrainValidationSplitModel] with TrainValidationSplitParams

:: Experimental :: Model from train validation split.

Annotations
@Since( "1.5.0" ) @Experimental()
Source
TrainValidationSplit.scala
Linear Supertypes
TrainValidationSplitParams, ValidatorParams, Model[TrainValidationSplitModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. TrainValidationSplitModel
  2. TrainValidationSplitParams
  3. ValidatorParams
  4. Model
  5. Transformer
  6. PipelineStage
  7. Logging
  8. Params
  9. Serializable
  10. Serializable
  11. Identifiable
  12. AnyRef
  13. Any
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  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. final def $[T](param: Param[T]): T

    An alias for getOrDefault().

    An alias for getOrDefault().

    Attributes
    protected
    Definition Classes
    Params
  5. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  6. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  8. val bestModel: Model[_]

    Estimator determined best model.

    Estimator determined best model.

    Annotations
    @Since( "1.5.0" )
  9. final def clear(param: Param[_]): TrainValidationSplitModel.this.type

    Clears the user-supplied value for the input param.

    Clears the user-supplied value for the input param.

    Definition Classes
    Params
  10. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  11. def copy(extra: ParamMap): TrainValidationSplitModel

    Creates a copy of this instance with the same UID and some extra params.

    Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly.

    Definition Classes
    TrainValidationSplitModelModelTransformerPipelineStageParams
    Annotations
    @Since( "1.5.0" )
    See also

    defaultCopy()

  12. def copyValues[T <: Params](to: T, extra: ParamMap = ParamMap.empty): T

    Copies param values from this instance to another instance for params shared by them.

    Copies param values from this instance to another instance for params shared by them.

    This handles default Params and explicitly set Params separately. Default Params are copied from and to defaultParamMap, and explicitly set Params are copied from and to paramMap. Warning: This implicitly assumes that this Params instance and the target instance share the same set of default Params.

    to

    the target instance, which should work with the same set of default Params as this source instance

    extra

    extra params to be copied to the target's paramMap

    returns

    the target instance with param values copied

    Attributes
    protected
    Definition Classes
    Params
  13. final def defaultCopy[T <: Params](extra: ParamMap): T

    Default implementation of copy with extra params.

    Default implementation of copy with extra params. It tries to create a new instance with the same UID. Then it copies the embedded and extra parameters over and returns the new instance.

    Attributes
    protected
    Definition Classes
    Params
  14. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  15. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  16. val estimator: Param[Estimator[_]]

    param for the estimator to be validated

    param for the estimator to be validated

    Definition Classes
    ValidatorParams
  17. val estimatorParamMaps: Param[Array[ParamMap]]

    param for estimator param maps

    param for estimator param maps

    Definition Classes
    ValidatorParams
  18. val evaluator: Param[Evaluator]

    param for the evaluator used to select hyper-parameters that maximize the validated metric

    param for the evaluator used to select hyper-parameters that maximize the validated metric

    Definition Classes
    ValidatorParams
  19. def explainParam(param: Param[_]): String

    Explains a param.

    Explains a param.

    param

    input param, must belong to this instance.

    returns

    a string that contains the input param name, doc, and optionally its default value and the user-supplied value

    Definition Classes
    Params
  20. def explainParams(): String

    Explains all params of this instance.

    Explains all params of this instance.

    Definition Classes
    Params
    See also

    explainParam()

  21. final def extractParamMap(): ParamMap

    extractParamMap with no extra values.

    extractParamMap with no extra values.

    Definition Classes
    Params
  22. final def extractParamMap(extra: ParamMap): ParamMap

    Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.

    Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values < user-supplied values < extra.

    Definition Classes
    Params
  23. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  24. final def get[T](param: Param[T]): Option[T]

    Optionally returns the user-supplied value of a param.

    Optionally returns the user-supplied value of a param.

    Definition Classes
    Params
  25. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  26. final def getDefault[T](param: Param[T]): Option[T]

    Gets the default value of a parameter.

    Gets the default value of a parameter.

    Definition Classes
    Params
  27. def getEstimator: Estimator[_]

    Definition Classes
    ValidatorParams
  28. def getEstimatorParamMaps: Array[ParamMap]

    Definition Classes
    ValidatorParams
  29. def getEvaluator: Evaluator

    Definition Classes
    ValidatorParams
  30. final def getOrDefault[T](param: Param[T]): T

    Gets the value of a param in the embedded param map or its default value.

    Gets the value of a param in the embedded param map or its default value. Throws an exception if neither is set.

    Definition Classes
    Params
  31. def getParam(paramName: String): Param[Any]

    Gets a param by its name.

    Gets a param by its name.

    Definition Classes
    Params
  32. def getTrainRatio: Double

    Definition Classes
    TrainValidationSplitParams
  33. final def hasDefault[T](param: Param[T]): Boolean

    Tests whether the input param has a default value set.

    Tests whether the input param has a default value set.

    Definition Classes
    Params
  34. def hasParam(paramName: String): Boolean

    Tests whether this instance contains a param with a given name.

    Tests whether this instance contains a param with a given name.

    Definition Classes
    Params
  35. def hasParent: Boolean

    Indicates whether this Model has a corresponding parent.

    Indicates whether this Model has a corresponding parent.

    Definition Classes
    Model
  36. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  37. final def isDefined(param: Param[_]): Boolean

    Checks whether a param is explicitly set or has a default value.

    Checks whether a param is explicitly set or has a default value.

    Definition Classes
    Params
  38. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  39. final def isSet(param: Param[_]): Boolean

    Checks whether a param is explicitly set.

    Checks whether a param is explicitly set.

    Definition Classes
    Params
  40. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging
  41. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging
  42. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  43. def logDebug(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  44. def logError(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  45. def logError(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  46. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  47. def logInfo(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  48. def logName: String

    Attributes
    protected
    Definition Classes
    Logging
  49. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  50. def logTrace(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  51. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  52. def logWarning(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  53. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  54. final def notify(): Unit

    Definition Classes
    AnyRef
  55. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  56. lazy val params: Array[Param[_]]

    Returns all params sorted by their names.

    Returns all params sorted by their names. The default implementation uses Java reflection to list all public methods that have no arguments and return Param.

    Note: Developer should not use this method in constructor because we cannot guarantee that this variable gets initialized before other params.

    Definition Classes
    Params
  57. var parent: Estimator[TrainValidationSplitModel]

    The parent estimator that produced this model.

    The parent estimator that produced this model. Note: For ensembles' component Models, this value can be null.

    Definition Classes
    Model
  58. final def set(paramPair: ParamPair[_]): TrainValidationSplitModel.this.type

    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

    Attributes
    protected
    Definition Classes
    Params
  59. final def set(param: String, value: Any): TrainValidationSplitModel.this.type

    Sets a parameter (by name) in the embedded param map.

    Sets a parameter (by name) in the embedded param map.

    Attributes
    protected
    Definition Classes
    Params
  60. final def set[T](param: Param[T], value: T): TrainValidationSplitModel.this.type

    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

    Definition Classes
    Params
  61. final def setDefault(paramPairs: ParamPair[_]*): TrainValidationSplitModel.this.type

    Sets default values for a list of params.

    Sets default values for a list of params.

    Note: Java developers should use the single-parameter setDefault(). Annotating this with varargs can cause compilation failures due to a Scala compiler bug. See SPARK-9268.

    paramPairs

    a list of param pairs that specify params and their default values to set respectively. Make sure that the params are initialized before this method gets called.

    Attributes
    protected
    Definition Classes
    Params
  62. final def setDefault[T](param: Param[T], value: T): TrainValidationSplitModel.this.type

    Sets a default value for a param.

    Sets a default value for a param.

    param

    param to set the default value. Make sure that this param is initialized before this method gets called.

    value

    the default value

    Attributes
    protected
    Definition Classes
    Params
  63. def setParent(parent: Estimator[TrainValidationSplitModel]): TrainValidationSplitModel

    Sets the parent of this model (Java API).

    Sets the parent of this model (Java API).

    Definition Classes
    Model
  64. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  65. def toString(): String

    Definition Classes
    Identifiable → AnyRef → Any
  66. val trainRatio: DoubleParam

    Param for ratio between train and validation data.

    Param for ratio between train and validation data. Must be between 0 and 1. Default: 0.75

    Definition Classes
    TrainValidationSplitParams
  67. def transform(dataset: DataFrame): DataFrame

    Transforms the input dataset.

    Transforms the input dataset.

    Definition Classes
    TrainValidationSplitModelTransformer
    Annotations
    @Since( "1.5.0" )
  68. def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame

    Transforms the dataset with provided parameter map as additional parameters.

    Transforms the dataset with provided parameter map as additional parameters.

    dataset

    input dataset

    paramMap

    additional parameters, overwrite embedded params

    returns

    transformed dataset

    Definition Classes
    Transformer
  69. def transform(dataset: DataFrame, firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

    Transforms the dataset with optional parameters

    Transforms the dataset with optional parameters

    dataset

    input dataset

    firstParamPair

    the first param pair, overwrite embedded params

    otherParamPairs

    other param pairs, overwrite embedded params

    returns

    transformed dataset

    Definition Classes
    Transformer
    Annotations
    @varargs()
  70. def transformSchema(schema: StructType): StructType

    :: DeveloperApi ::

    :: DeveloperApi ::

    Derives the output schema from the input schema.

    Definition Classes
    TrainValidationSplitModelPipelineStage
    Annotations
    @Since( "1.5.0" )
  71. def transformSchema(schema: StructType, logging: Boolean): StructType

    :: DeveloperApi ::

    :: DeveloperApi ::

    Derives the output schema from the input schema and parameters, optionally with logging.

    This should be optimistic. If it is unclear whether the schema will be valid, then it should be assumed valid until proven otherwise.

    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  72. val uid: String

    Id.

    Id.

    Definition Classes
    TrainValidationSplitModelIdentifiable
    Annotations
    @Since( "1.5.0" )
  73. def validateParams(): Unit

    Validates parameter values stored internally.

    Validates parameter values stored internally. Raise an exception if any parameter value is invalid.

    This only needs to check for interactions between parameters. Parameter value checks which do not depend on other parameters are handled by Param.validate(). This method does not handle input/output column parameters; those are checked during schema validation.

    Definition Classes
    TrainValidationSplitModelParams
    Annotations
    @Since( "1.5.0" )
  74. val validationMetrics: Array[Double]

    Evaluated validation metrics.

    Evaluated validation metrics.

    Annotations
    @Since( "1.5.0" )
  75. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  76. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  77. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from TrainValidationSplitParams

Inherited from ValidatorParams

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Parameters

A list of (hyper-)parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters, respectively.

Members

Parameter getters