org.apache.spark.ml.tuning

CrossValidator

class CrossValidator extends Estimator[CrossValidatorModel] with CrossValidatorParams with Logging

:: AlphaComponent :: K-fold cross validation.

Annotations
@AlphaComponent()
Linear Supertypes
CrossValidatorParams, Estimator[CrossValidatorModel], Params, Identifiable, PipelineStage, Logging, Serializable, Serializable, AnyRef, Any
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Inherited
  1. CrossValidator
  2. CrossValidatorParams
  3. Estimator
  4. Params
  5. Identifiable
  6. PipelineStage
  7. Logging
  8. Serializable
  9. Serializable
  10. AnyRef
  11. Any
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Instance Constructors

  1. new CrossValidator()

Value Members

  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 ==(arg0: AnyRef): Boolean

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

    Definition Classes
    Any
  6. def addOutputColumn(schema: StructType, colName: String, dataType: DataType): StructType

    Attributes
    protected
    Definition Classes
    Params
  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  8. def checkInputColumn(schema: StructType, colName: String, dataType: DataType): Unit

    Check whether the given schema contains an input column.

    Check whether the given schema contains an input column.

    colName

    Parameter name for the input column.

    dataType

    SQL DataType of the input column.

    Attributes
    protected
    Definition Classes
    Params
  9. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  10. final def eq(arg0: AnyRef): Boolean

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

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

    param for the estimator to be cross-validated

    param for the estimator to be cross-validated

    Definition Classes
    CrossValidatorParams
  13. val estimatorParamMaps: Param[Array[ParamMap]]

    param for estimator param maps

    param for estimator param maps

    Definition Classes
    CrossValidatorParams
  14. val evaluator: Param[Evaluator]

    param for the evaluator for selection

    param for the evaluator for selection

    Definition Classes
    CrossValidatorParams
  15. def explainParams(): String

    Returns the documentation of all params.

    Returns the documentation of all params.

    Definition Classes
    Params
  16. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  17. def fit(dataset: DataFrame, paramMap: ParamMap): CrossValidatorModel

    Fits a single model to the input data with provided parameter map.

    Fits a single model to the input data with provided parameter map.

    dataset

    input dataset

    paramMap

    Parameter map. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted model

    Definition Classes
    CrossValidatorEstimator
  18. def fit(dataset: DataFrame, paramMaps: Array[ParamMap]): Seq[CrossValidatorModel]

    Fits multiple models to the input data with multiple sets of parameters.

    Fits multiple models to the input data with multiple sets of parameters. The default implementation uses a for loop on each parameter map. Subclasses could overwrite this to optimize multi-model training.

    dataset

    input dataset

    paramMaps

    An array of parameter maps. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted models, matching the input parameter maps

    Definition Classes
    Estimator
  19. def fit(dataset: DataFrame, paramPairs: ParamPair[_]*): CrossValidatorModel

    Fits a single model to the input data with optional parameters.

    Fits a single model to the input data with optional parameters.

    dataset

    input dataset

    paramPairs

    Optional list of param pairs. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted model

    Definition Classes
    Estimator
    Annotations
    @varargs()
  20. def get[T](param: Param[T]): T

    Gets the value of a parameter in the embedded param map.

    Gets the value of a parameter in the embedded param map.

    Attributes
    protected
    Definition Classes
    Params
  21. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  22. def getEstimator: Estimator[_]

    Definition Classes
    CrossValidatorParams
  23. def getEstimatorParamMaps: Array[ParamMap]

    Definition Classes
    CrossValidatorParams
  24. def getEvaluator: Evaluator

    Definition Classes
    CrossValidatorParams
  25. def getNumFolds: Int

    Definition Classes
    CrossValidatorParams
  26. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  27. final def isInstanceOf[T0]: Boolean

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

    Checks whether a param is explicitly set.

    Checks whether a param is explicitly set.

    Definition Classes
    Params
  29. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging
  30. def log: Logger

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

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

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

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

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

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

    Attributes
    protected
    Definition Classes
    Logging
  37. def logName: String

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

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

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

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

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

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

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

    Definition Classes
    AnyRef
  45. val numFolds: IntParam

    param for number of folds for cross validation

    param for number of folds for cross validation

    Definition Classes
    CrossValidatorParams
  46. val paramMap: ParamMap

    Internal param map.

    Internal param map.

    Attributes
    protected
    Definition Classes
    Params
  47. def params: Array[Param[_]]

    Returns all params.

    Returns all params.

    Definition Classes
    Params
  48. def set[T](param: Param[T], value: T): CrossValidator.this.type

    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

    Attributes
    protected
    Definition Classes
    Params
  49. def setEstimator(value: Estimator[_]): CrossValidator.this.type

  50. def setEstimatorParamMaps(value: Array[ParamMap]): CrossValidator.this.type

  51. def setEvaluator(value: Evaluator): CrossValidator.this.type

  52. def setNumFolds(value: Int): CrossValidator.this.type

  53. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  54. def toString(): String

    Definition Classes
    AnyRef → Any
  55. def transformSchema(schema: StructType, paramMap: ParamMap): StructType

    :: DeveloperAPI ::

    :: DeveloperAPI ::

    Derives the output schema from the input schema and parameters. The schema describes the columns and types of the data.

    schema

    Input schema to this stage

    paramMap

    Parameters passed to this stage

    returns

    Output schema from this stage

    Definition Classes
    CrossValidatorPipelineStage
  56. def transformSchema(schema: StructType, paramMap: ParamMap, logging: Boolean): StructType

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

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

    Attributes
    protected
    Definition Classes
    PipelineStage
  57. def validate(): Unit

    Validates parameter values stored internally.

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

    Definition Classes
    Params
  58. def validate(paramMap: ParamMap): Unit

    Validates parameter values stored internally plus the input parameter map.

    Validates parameter values stored internally plus the input parameter map. Raises an exception if any parameter is invalid.

    Definition Classes
    Params
  59. final def wait(): Unit

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

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from CrossValidatorParams

Inherited from Estimator[CrossValidatorModel]

Inherited from Params

Inherited from Identifiable

Inherited from PipelineStage

Inherited from Logging

Inherited from Serializable

Inherited from Serializable

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 setters

Parameter getters