Class/Object

org.apache.spark.ml.classification

OneVsRest

Related Docs: object OneVsRest | package classification

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final class OneVsRest extends Estimator[OneVsRestModel] with OneVsRestParams with HasParallelism with MLWritable

Reduction of Multiclass Classification to Binary Classification. Performs reduction using one against all strategy. For a multiclass classification with k classes, train k models (one per class). Each example is scored against all k models and the model with highest score is picked to label the example.

Annotations
@Since( "1.4.0" )
Source
OneVsRest.scala
Linear Supertypes
MLWritable, HasParallelism, OneVsRestParams, HasWeightCol, ClassifierTypeTrait, ClassifierParams, HasRawPredictionCol, PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Estimator[OneVsRestModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. OneVsRest
  2. MLWritable
  3. HasParallelism
  4. OneVsRestParams
  5. HasWeightCol
  6. ClassifierTypeTrait
  7. ClassifierParams
  8. HasRawPredictionCol
  9. PredictorParams
  10. HasPredictionCol
  11. HasFeaturesCol
  12. HasLabelCol
  13. Estimator
  14. PipelineStage
  15. Logging
  16. Params
  17. Serializable
  18. Serializable
  19. Identifiable
  20. AnyRef
  21. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new OneVsRest()

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    Annotations
    @Since( "1.4.0" )
  2. new OneVsRest(uid: String)

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    Annotations
    @Since( "1.4.0" )

Type Members

  1. type ClassifierType = Classifier[F, E, M] forSome {type F, type M <: ClassificationModel[F, M], type E <: Classifier[F, E, M]}

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    Definition Classes
    ClassifierTypeTrait

Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

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

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    An alias for getOrDefault().

    An alias for getOrDefault().

    Attributes
    protected
    Definition Classes
    Params
  4. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  6. val classifier: Param[ClassifierType]

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    param for the base binary classifier that we reduce multiclass classification into.

    param for the base binary classifier that we reduce multiclass classification into. The base classifier input and output columns are ignored in favor of the ones specified in OneVsRest.

    Definition Classes
    OneVsRestParams
  7. final def clear(param: Param[_]): OneVsRest.this.type

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    Clears the user-supplied value for the input param.

    Clears the user-supplied value for the input param.

    Definition Classes
    Params
  8. def clone(): AnyRef

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

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    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. See defaultCopy().

    Definition Classes
    OneVsRestEstimatorPipelineStageParams
    Annotations
    @Since( "1.4.1" )
  10. def copyValues[T <: Params](to: T, extra: ParamMap = ParamMap.empty): T

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    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
  11. final def defaultCopy[T <: Params](extra: ParamMap): T

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    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
  12. final def eq(arg0: AnyRef): Boolean

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

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    Definition Classes
    AnyRef → Any
  14. def explainParam(param: Param[_]): String

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    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
  15. def explainParams(): String

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    Explains all params of this instance.

    Explains all params of this instance. See explainParam().

    Definition Classes
    Params
  16. final def extractParamMap(): ParamMap

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    extractParamMap with no extra values.

    extractParamMap with no extra values.

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

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    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 less than user-supplied values less than extra.

    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 less than user-supplied values less than extra.

    Definition Classes
    Params
  18. final val featuresCol: Param[String]

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    Param for features column name.

    Param for features column name.

    Definition Classes
    HasFeaturesCol
  19. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  20. def fit(dataset: Dataset[_]): OneVsRestModel

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    Fits a model to the input data.

    Fits a model to the input data.

    Definition Classes
    OneVsRestEstimator
    Annotations
    @Since( "2.0.0" )
  21. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[OneVsRestModel]

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    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 override 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
    Annotations
    @Since( "2.0.0" )
  22. def fit(dataset: Dataset[_], paramMap: ParamMap): OneVsRestModel

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    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
    Estimator
    Annotations
    @Since( "2.0.0" )
  23. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): OneVsRestModel

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    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

    firstParamPair

    the first param pair, overrides embedded params

    otherParamPairs

    other param pairs. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted model

    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  24. final def get[T](param: Param[T]): Option[T]

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    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[_]

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    Definition Classes
    AnyRef → Any
  26. def getClassifier: ClassifierType

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    Definition Classes
    OneVsRestParams
  27. final def getDefault[T](param: Param[T]): Option[T]

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    Gets the default value of a parameter.

    Gets the default value of a parameter.

    Definition Classes
    Params
  28. final def getFeaturesCol: String

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    Definition Classes
    HasFeaturesCol
  29. final def getLabelCol: String

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

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    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 getParallelism: Int

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    Definition Classes
    HasParallelism
  32. def getParam(paramName: String): Param[Any]

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    Gets a param by its name.

    Gets a param by its name.

    Definition Classes
    Params
  33. final def getPredictionCol: String

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    Definition Classes
    HasPredictionCol
  34. final def getRawPredictionCol: String

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    Definition Classes
    HasRawPredictionCol
  35. final def getWeightCol: String

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    Definition Classes
    HasWeightCol
  36. final def hasDefault[T](param: Param[T]): Boolean

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    Tests whether the input param has a default value set.

    Tests whether the input param has a default value set.

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

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    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
  38. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  39. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean = false): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  40. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  41. final def isDefined(param: Param[_]): Boolean

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    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
  42. final def isInstanceOf[T0]: Boolean

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

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    Checks whether a param is explicitly set.

    Checks whether a param is explicitly set.

    Definition Classes
    Params
  44. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  45. final val labelCol: Param[String]

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    Param for label column name.

    Param for label column name.

    Definition Classes
    HasLabelCol
  46. def log: Logger

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

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  53. def logName: String

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

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

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

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

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

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

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

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    Definition Classes
    AnyRef
  61. val parallelism: IntParam

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    The number of threads to use when running parallel algorithms.

    The number of threads to use when running parallel algorithms. Default is 1 for serial execution

    Definition Classes
    HasParallelism
  62. lazy val params: Array[Param[_]]

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    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.

    Definition Classes
    Params
    Note

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

  63. final val predictionCol: Param[String]

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    Param for prediction column name.

    Param for prediction column name.

    Definition Classes
    HasPredictionCol
  64. final val rawPredictionCol: Param[String]

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    Param for raw prediction (a.k.a.

    Param for raw prediction (a.k.a. confidence) column name.

    Definition Classes
    HasRawPredictionCol
  65. def save(path: String): Unit

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    Saves this ML instance to the input path, a shortcut of write.save(path).

    Saves this ML instance to the input path, a shortcut of write.save(path).

    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  66. final def set(paramPair: ParamPair[_]): OneVsRest.this.type

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    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

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

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    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
  68. final def set[T](param: Param[T], value: T): OneVsRest.this.type

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    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

    Definition Classes
    Params
  69. def setClassifier(value: Classifier[_, _, _]): OneVsRest.this.type

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    Annotations
    @Since( "1.4.0" )
  70. final def setDefault(paramPairs: ParamPair[_]*): OneVsRest.this.type

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    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
  71. final def setDefault[T](param: Param[T], value: T): OneVsRest.this.type

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    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
  72. def setFeaturesCol(value: String): OneVsRest.this.type

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    Annotations
    @Since( "1.5.0" )
  73. def setLabelCol(value: String): OneVsRest.this.type

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    Annotations
    @Since( "1.5.0" )
  74. def setParallelism(value: Int): OneVsRest.this.type

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    The implementation of parallel one vs.

    The implementation of parallel one vs. rest runs the classification for each class in a separate threads.

    Annotations
    @Since( "2.3.0" )
  75. def setPredictionCol(value: String): OneVsRest.this.type

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    Annotations
    @Since( "1.5.0" )
  76. def setRawPredictionCol(value: String): OneVsRest.this.type

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    Annotations
    @Since( "2.4.0" )
  77. def setWeightCol(value: String): OneVsRest.this.type

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    Sets the value of param weightCol.

    Sets the value of param weightCol.

    This is ignored if weight is not supported by classifier. If this is not set or empty, we treat all instance weights as 1.0. Default is not set, so all instances have weight one.

    Annotations
    @Since( "2.3.0" )
  78. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  79. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any
  80. def transformSchema(schema: StructType): StructType

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    :: DeveloperApi ::

    :: DeveloperApi ::

    Check transform validity and derive the output schema from the input schema.

    We check validity for interactions between parameters during transformSchema and raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled by Param.validate().

    Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.

    Definition Classes
    OneVsRestPipelineStage
    Annotations
    @Since( "1.4.0" )
  81. def transformSchema(schema: StructType, logging: Boolean): StructType

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    :: 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()
  82. val uid: String

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    An immutable unique ID for the object and its derivatives.

    An immutable unique ID for the object and its derivatives.

    Definition Classes
    OneVsRestIdentifiable
    Annotations
    @Since( "1.4.0" )
  83. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType

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    Validates and transforms the input schema with the provided param map.

    Validates and transforms the input schema with the provided param map.

    schema

    input schema

    fitting

    whether this is in fitting

    featuresDataType

    SQL DataType for FeaturesType. E.g., VectorUDT for vector features.

    returns

    output schema

    Attributes
    protected
    Definition Classes
    ClassifierParams → PredictorParams
  84. final def wait(): Unit

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

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  87. final val weightCol: Param[String]

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    Param for weight column name.

    Param for weight column name. If this is not set or empty, we treat all instance weights as 1.0.

    Definition Classes
    HasWeightCol
  88. def write: MLWriter

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    Returns an MLWriter instance for this ML instance.

    Returns an MLWriter instance for this ML instance.

    Definition Classes
    OneVsRestMLWritable
    Annotations
    @Since( "2.0.0" )

Inherited from MLWritable

Inherited from HasParallelism

Inherited from OneVsRestParams

Inherited from HasWeightCol

Inherited from ClassifierTypeTrait

Inherited from ClassifierParams

Inherited from HasRawPredictionCol

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Estimator[OneVsRestModel]

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 setters

Parameter getters

(expert-only) Parameters

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

(expert-only) Parameter setters

(expert-only) Parameter getters