Class

com.salesforce.op.stages.impl.classification

OpNaiveBayes

Related Doc: package classification

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class OpNaiveBayes extends OpPredictorWrapper[NaiveBayes, NaiveBayesModel] with OpNaiveBayesParams

Wrapper for spark Naive Bayes org.apache.spark.ml.classification.NaiveBayesModel

Linear Supertypes
OpNaiveBayesParams, NaiveBayesParams, HasWeightCol, PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, OpPredictorWrapper[NaiveBayes, NaiveBayesModel], SparkWrapperParams[NaiveBayes], OpPipelineStage2[RealNN, OPVector, Prediction], HasIn2, HasIn1, OpPipelineStage[Prediction], OpPipelineStageBase, MLWritable, OpPipelineStageParams, InputParams, Estimator[OpPredictorWrapperModel[NaiveBayesModel]], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. OpNaiveBayes
  2. OpNaiveBayesParams
  3. NaiveBayesParams
  4. HasWeightCol
  5. PredictorParams
  6. HasPredictionCol
  7. HasFeaturesCol
  8. HasLabelCol
  9. OpPredictorWrapper
  10. SparkWrapperParams
  11. OpPipelineStage2
  12. HasIn2
  13. HasIn1
  14. OpPipelineStage
  15. OpPipelineStageBase
  16. MLWritable
  17. OpPipelineStageParams
  18. InputParams
  19. Estimator
  20. PipelineStage
  21. Logging
  22. Params
  23. Serializable
  24. Serializable
  25. Identifiable
  26. AnyRef
  27. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new OpNaiveBayes(uid: String = UID[OpNaiveBayes])

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    uid

    stage uid

Type Members

  1. final type InputFeatures = (FeatureLike[RealNN], FeatureLike[OPVector])

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    Input Features type

    Input Features type

    Definition Classes
    OpPipelineStage2OpPipelineStageInputParams
  2. final type OutputFeatures = FeatureLike[Prediction]

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    Definition Classes
    OpPipelineStageOpPipelineStageBase

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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    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. final def checkInputLength(features: Array[_]): Boolean

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    Checks the input length

    Checks the input length

    features

    input features

    returns

    true is input size as expected, false otherwise

    Definition Classes
    OpPipelineStage2InputParams
  7. def checkSerializable: Try[Unit]

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    Check if the stage is serializable

    Check if the stage is serializable

    returns

    Failure if not serializable

    Definition Classes
    OpPipelineStageBase
  8. final def clear(param: Param[_]): OpNaiveBayes.this.type

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    Definition Classes
    Params
  9. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  10. final def copy(extra: ParamMap): OpNaiveBayes.this.type

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    This method is used to make a copy of the instance with new parameters in several methods in spark internals Default will find the constructor and make a copy for any class (AS LONG AS ALL CONSTRUCTOR PARAMS ARE VALS, this is why type tags are written as implicit vals in base classes).

    This method is used to make a copy of the instance with new parameters in several methods in spark internals Default will find the constructor and make a copy for any class (AS LONG AS ALL CONSTRUCTOR PARAMS ARE VALS, this is why type tags are written as implicit vals in base classes).

    Note: that the convention in spark is to have the uid be a constructor argument, so that copies will share a uid with the original (developers should follow this convention).

    extra

    new parameters want to add to instance

    returns

    a new instance with the same uid

    Definition Classes
    OpPipelineStageBase → Params
  11. def copyValues[T <: Params](to: T, extra: ParamMap): T

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

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

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

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

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    Definition Classes
    Params
  16. def explainParams(): String

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

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

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

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    Definition Classes
    HasFeaturesCol
  20. def finalize(): Unit

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

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    Function that fits the binary model

    Function that fits the binary model

    Definition Classes
    OpPredictorWrapper → Estimator
  22. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[OpPredictorWrapperModel[NaiveBayesModel]]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  23. def fit(dataset: Dataset[_], paramMap: ParamMap): OpPredictorWrapperModel[NaiveBayesModel]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  24. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): OpPredictorWrapperModel[NaiveBayesModel]

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

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

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

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    Definition Classes
    Params
  28. final def getFeaturesCol: String

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    Definition Classes
    HasFeaturesCol
  29. final def getInputFeature[T <: FeatureType](i: Int): Option[FeatureLike[T]]

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    Gets an input feature Note: this method IS NOT safe to use outside the driver, please use getTransientFeature method instead

    Gets an input feature Note: this method IS NOT safe to use outside the driver, please use getTransientFeature method instead

    returns

    array of features

    Definition Classes
    InputParams
    Exceptions thrown

    NoSuchElementException if the features are not set

    RuntimeException in case one of the features is null

  30. final def getInputFeatures(): Array[OPFeature]

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    Gets the input features Note: this method IS NOT safe to use outside the driver, please use getTransientFeatures method instead

    Gets the input features Note: this method IS NOT safe to use outside the driver, please use getTransientFeatures method instead

    returns

    array of features

    Definition Classes
    InputParams
    Exceptions thrown

    NoSuchElementException if the features are not set

    RuntimeException in case one of the features is null

  31. final def getInputSchema(): StructType

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    Definition Classes
    OpPipelineStageParams
  32. final def getLabelCol: String

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    Definition Classes
    HasLabelCol
  33. final def getMetadata(): Metadata

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    Definition Classes
    OpPipelineStageParams
  34. final def getModelType: String

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    Definition Classes
    NaiveBayesParams
  35. final def getOrDefault[T](param: Param[T]): T

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    Definition Classes
    Params
  36. def getOutput(): FeatureLike[Prediction]

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    Output features that will be created by this stage

    Output features that will be created by this stage

    returns

    feature of type OutputFeatures

    Definition Classes
    OpPipelineStage2OpPipelineStageBase
  37. final def getOutputFeatureName: String

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    Name of output feature (i.e.

    Name of output feature (i.e. column created by this stage)

    Definition Classes
    OpPipelineStage
  38. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  39. final def getPredictionCol: String

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    Definition Classes
    HasPredictionCol
  40. final def getSmoothing: Double

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    Definition Classes
    NaiveBayesParams
  41. def getSparkMlStage(): Option[NaiveBayes]

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    Method to access the spark stage being wrapped

    Method to access the spark stage being wrapped

    returns

    Option of spark ml stage

    Definition Classes
    SparkWrapperParams
  42. def getStageSavePath(): Option[String]

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    Gets a save path for wrapped spark stage

    Gets a save path for wrapped spark stage

    Definition Classes
    SparkWrapperParams
  43. final def getTransientFeature(i: Int): Option[TransientFeature]

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    Gets an input feature at index i

    Gets an input feature at index i

    i

    input index

    returns

    maybe an input feature

    Definition Classes
    InputParams
  44. final def getTransientFeatures(): Array[TransientFeature]

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    Gets the input Features

    Gets the input Features

    returns

    input features

    Definition Classes
    InputParams
  45. final def getWeightCol: String

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

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

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    Definition Classes
    Params
  48. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  49. final def in1: TransientFeature

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    Attributes
    protected
    Definition Classes
    HasIn1
  50. final def in2: TransientFeature

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    Attributes
    protected
    Definition Classes
    HasIn2
  51. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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

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    Attributes
    protected
    Definition Classes
    Logging
  53. final def inputAsArray(in: InputFeatures): Array[OPFeature]

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    Function to convert InputFeatures to an Array of FeatureLike

    Function to convert InputFeatures to an Array of FeatureLike

    returns

    an Array of FeatureLike

    Definition Classes
    OpPipelineStage2InputParams
  54. val inputParam1Name: String

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    Definition Classes
    OpPredictorWrapper
  55. val inputParam2Name: String

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    Definition Classes
    OpPredictorWrapper
  56. final def isDefined(param: Param[_]): Boolean

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

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

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    Definition Classes
    Params
  59. def isTraceEnabled(): Boolean

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

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    Definition Classes
    HasLabelCol
  61. def log: Logger

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

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  68. def logName: String

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  73. final val modelType: Param[String]

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    Definition Classes
    NaiveBayesParams
  74. final def ne(arg0: AnyRef): Boolean

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

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

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    Definition Classes
    AnyRef
  77. def onGetMetadata(): Unit

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    Function to be called on getMetadata

    Function to be called on getMetadata

    Attributes
    protected
    Definition Classes
    OpPipelineStageParams
  78. def onSetInput(): Unit

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    Function to be called on setInput

    Function to be called on setInput

    Attributes
    protected
    Definition Classes
    OpNaiveBayesOpPipelineStageBase
  79. val operationName: String

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    Short unique name of the operation this stage performs

    Short unique name of the operation this stage performs

    returns

    operation name

    Definition Classes
    OpPredictorWrapperOpPipelineStageBase
  80. final def outputAsArray(out: OutputFeatures): Array[OPFeature]

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    Function to convert OutputFeatures to an Array of FeatureLike

    Function to convert OutputFeatures to an Array of FeatureLike

    returns

    an Array of FeatureLike

    Definition Classes
    OpPipelineStageOpPipelineStageBase
  81. def outputFeatureUid: String

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    Attributes
    protected[com.salesforce.op]
    Definition Classes
    OpPipelineStage2OpPipelineStage
  82. def outputIsResponse: Boolean

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    Should output feature be a response? Yes, if any of the input features are.

    Should output feature be a response? Yes, if any of the input features are.

    returns

    true if the the output feature should be a response

    Definition Classes
    OpPipelineStage
  83. val outputParamName: String

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    Definition Classes
    OpPredictorWrapper
  84. lazy val params: Array[Param[_]]

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    Definition Classes
    Params
  85. final val predictionCol: Param[String]

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    Definition Classes
    HasPredictionCol
  86. val predictor: NaiveBayes

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    the predictor to wrap

    the predictor to wrap

    Definition Classes
    OpPredictorWrapper
  87. def save(path: String): Unit

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Params
  93. final def setInput(features: InputFeatures): OpNaiveBayes.this.type

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    Input features that will be used by the stage

    Input features that will be used by the stage

    returns

    feature of type InputFeatures

    Definition Classes
    OpPipelineStageBase
  94. final def setInputFeatures[S <: OPFeature](features: Array[S]): OpNaiveBayes.this.type

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    Sets input features

    Sets input features

    S

    feature like type

    features

    array of input features

    returns

    this stage

    Attributes
    protected
    Definition Classes
    InputParams
  95. final def setMetadata(m: Metadata): OpNaiveBayes.this.type

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    Definition Classes
    OpPipelineStageParams
  96. def setModelType(value: String): OpNaiveBayes.this.type

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    Set the model type using a string (case-sensitive).

    Set the model type using a string (case-sensitive). Supported options: "multinomial" and "bernoulli". Default is "multinomial"

  97. def setOutputFeatureName(name: String): OpNaiveBayes.this.type

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    Definition Classes
    OpPipelineStage
  98. def setSmoothing(value: Double): OpNaiveBayes.this.type

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    Set the smoothing parameter.

    Set the smoothing parameter. Default is 1.0.

  99. def setSparkMlStage(stage: Option[NaiveBayes]): OpNaiveBayes.this.type

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    Attributes
    protected
    Definition Classes
    SparkWrapperParams
  100. def setStageSavePath(path: String): OpNaiveBayes.this.type

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    Sets a save path for wrapped spark stage

    Sets a save path for wrapped spark stage

    Definition Classes
    SparkWrapperParams
  101. def setWeightCol(value: String): OpNaiveBayes.this.type

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    Sets the value of param weightCol.

    Sets the value of param weightCol. 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.

  102. final val smoothing: DoubleParam

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    Definition Classes
    NaiveBayesParams
  103. final val sparkInputColParamNames: StringArrayParam

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    Definition Classes
    SparkWrapperParams
  104. final val sparkMlStage: SparkStageParam[NaiveBayes]

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    Definition Classes
    SparkWrapperParams
  105. final val sparkOutputColParamNames: StringArrayParam

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    Definition Classes
    SparkWrapperParams
  106. final def stageName: String

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    Stage unique name consisting of the stage operation name and uid

    Stage unique name consisting of the stage operation name and uid

    returns

    stage name

    Definition Classes
    OpPipelineStageBase
  107. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  108. def toString(): String

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

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    This function translates the input and output features into spark schema checks and changes that will occur on the underlying data frame

    This function translates the input and output features into spark schema checks and changes that will occur on the underlying data frame

    schema

    schema of the input data frame

    returns

    a new schema with the output features added

    Definition Classes
    OpPipelineStageBase
  110. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  111. implicit val tti1: scala.reflect.api.JavaUniverse.TypeTag[RealNN]

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    Definition Classes
    OpPredictorWrapper
  112. implicit val tti2: scala.reflect.api.JavaUniverse.TypeTag[OPVector]

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    Definition Classes
    OpPredictorWrapper
  113. implicit val tto: scala.reflect.api.JavaUniverse.TypeTag[Prediction]

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    Definition Classes
    OpPredictorWrapperOpPipelineStage2
  114. implicit val ttov: scala.reflect.api.JavaUniverse.TypeTag[Map[String, Double]]

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    Definition Classes
    OpPredictorWrapperOpPipelineStage2
  115. val uid: String

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    stage uid

    stage uid

    Definition Classes
    OpPredictorWrapper → Identifiable
  116. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType

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    Attributes
    protected
    Definition Classes
    PredictorParams
  117. final def wait(): Unit

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

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

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

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    Definition Classes
    HasWeightCol
  121. final def write: MLWriter

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    Definition Classes
    OpPipelineStageBase → MLWritable

Inherited from OpNaiveBayesParams

Inherited from NaiveBayesParams

Inherited from HasWeightCol

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from OpPredictorWrapper[NaiveBayes, NaiveBayesModel]

Inherited from SparkWrapperParams[NaiveBayes]

Inherited from HasIn2

Inherited from HasIn1

Inherited from OpPipelineStage[Prediction]

Inherited from OpPipelineStageBase

Inherited from MLWritable

Inherited from OpPipelineStageParams

Inherited from InputParams

Inherited from Estimator[OpPredictorWrapperModel[NaiveBayesModel]]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

setParam

Ungrouped