Class/Object

com.johnsnowlabs.nlp.annotators.pos.perceptron

PerceptronModel

Related Docs: object PerceptronModel | package perceptron

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class PerceptronModel extends AnnotatorModel[PerceptronModel] with PerceptronUtils

Part of speech tagger that might use different approaches

See https://github.com/JohnSnowLabs/spark-nlp/tree/master/src/test/scala/com/johnsnowlabs/nlp/annotators/pos/perceptron for further reference on how to use this API.

Linear Supertypes
PerceptronUtils, AnnotatorModel[PerceptronModel], CanBeLazy, RawAnnotator[PerceptronModel], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[PerceptronModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. PerceptronModel
  2. PerceptronUtils
  3. AnnotatorModel
  4. CanBeLazy
  5. RawAnnotator
  6. HasOutputAnnotationCol
  7. HasInputAnnotationCols
  8. HasOutputAnnotatorType
  9. ParamsAndFeaturesWritable
  10. HasFeatures
  11. DefaultParamsWritable
  12. MLWritable
  13. Model
  14. Transformer
  15. PipelineStage
  16. Logging
  17. Params
  18. Serializable
  19. Serializable
  20. Identifiable
  21. AnyRef
  22. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new PerceptronModel()

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  2. new PerceptronModel(uid: String)

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    uid

    Internal constructor requirement for serialization of params

Type Members

  1. type AnnotationContent = Seq[Row]

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    internal types to show Rows as a relevant StructType Should be deleted once Spark releases UserDefinedTypes to @developerAPI

    internal types to show Rows as a relevant StructType Should be deleted once Spark releases UserDefinedTypes to @developerAPI

    Attributes
    protected
    Definition Classes
    AnnotatorModel
  2. type AnnotatorType = String

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    Definition Classes
    HasOutputAnnotatorType

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. def $$[T](feature: StructFeature[T]): T

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    Attributes
    protected
    Definition Classes
    HasFeatures
  5. def $$[K, V](feature: MapFeature[K, V]): Map[K, V]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  6. def $$[T](feature: SetFeature[T]): Set[T]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  7. def $$[T](feature: ArrayFeature[T]): Array[T]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  8. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  9. def _transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame

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    Attributes
    protected
    Definition Classes
    AnnotatorModel
  10. def afterAnnotate(dataset: DataFrame): DataFrame

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    Attributes
    protected
    Definition Classes
    AnnotatorModel
  11. def annotate(annotations: Seq[Annotation]): Seq[Annotation]

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    One to one annotation standing from the Tokens perspective, to give each word a corresponding Tag

    One to one annotation standing from the Tokens perspective, to give each word a corresponding Tag

    annotations

    Annotations that correspond to inputAnnotationCols generated by previous annotators if any

    returns

    any number of annotations processed for every input annotation. Not necessary one to one relationship

    Definition Classes
    PerceptronModelAnnotatorModel
  12. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  13. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]

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    Attributes
    protected
    Definition Classes
    AnnotatorModel
  14. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean

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    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  15. final def clear(param: Param[_]): PerceptronModel.this.type

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    Definition Classes
    Params
  16. def clone(): AnyRef

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

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    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  18. def copyValues[T <: Params](to: T, extra: ParamMap): T

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

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    Attributes
    protected
    Definition Classes
    Params
  20. def dfAnnotate: UserDefinedFunction

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    Wraps annotate to happen inside SparkSQL user defined functions in order to act with org.apache.spark.sql.Column

    Wraps annotate to happen inside SparkSQL user defined functions in order to act with org.apache.spark.sql.Column

    returns

    udf function to be applied to inputCols using this annotator's annotate function as part of ML transformation

    Attributes
    protected
    Definition Classes
    AnnotatorModel
  21. final def eq(arg0: AnyRef): Boolean

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

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

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    Definition Classes
    Params
  24. def explainParams(): String

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    Definition Classes
    Params
  25. def extraValidate(structType: StructType): Boolean

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    Attributes
    protected
    Definition Classes
    RawAnnotator
  26. def extraValidateMsg: String

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    Override for additional custom schema checks

    Override for additional custom schema checks

    Attributes
    protected
    Definition Classes
    RawAnnotator
  27. final def extractParamMap(): ParamMap

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

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    Definition Classes
    Params
  29. val features: ArrayBuffer[Feature[_, _, _]]

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    Definition Classes
    HasFeatures
  30. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  31. def get[T](feature: StructFeature[T]): Option[T]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  32. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  33. def get[T](feature: SetFeature[T]): Option[Set[T]]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  34. def get[T](feature: ArrayFeature[T]): Option[Array[T]]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  35. final def get[T](param: Param[T]): Option[T]

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

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

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    Definition Classes
    Params
  38. def getInputCols: Array[String]

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    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  39. def getLazyAnnotator: Boolean

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    Definition Classes
    CanBeLazy
  40. def getModel: AveragedPerceptron

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  41. final def getOrDefault[T](param: Param[T]): T

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    Definition Classes
    Params
  42. final def getOutputCol: String

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    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  43. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  44. final def hasDefault[T](param: Param[T]): Boolean

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

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    Definition Classes
    Params
  46. def hasParent: Boolean

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    Definition Classes
    Model
  47. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  48. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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

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    Attributes
    protected
    Definition Classes
    Logging
  50. val inputAnnotatorTypes: Array[AnnotatorType]

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    Input annotator types : TOKEN, DOCUMENT

    Input annotator types : TOKEN, DOCUMENT

    Definition Classes
    PerceptronModelHasInputAnnotationCols
  51. final val inputCols: StringArrayParam

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    columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

    columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

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

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

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

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    Definition Classes
    Params
  55. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  56. val lazyAnnotator: BooleanParam

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    Definition Classes
    CanBeLazy
  57. def log: Logger

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

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  64. def logName: String

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  69. val model: StructFeature[AveragedPerceptron]

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    POS model

  70. def msgHelper(schema: StructType): String

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    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  71. final def ne(arg0: AnyRef): Boolean

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

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

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    Definition Classes
    AnyRef
  74. def onWrite(path: String, spark: SparkSession): Unit

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    Attributes
    protected
    Definition Classes
    ParamsAndFeaturesWritable
  75. val outputAnnotatorType: AnnotatorType

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    Output annotator types : POS

    Output annotator types : POS

    Definition Classes
    PerceptronModelHasOutputAnnotatorType
  76. final val outputCol: Param[String]

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    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  77. lazy val params: Array[Param[_]]

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    Definition Classes
    Params
  78. var parent: Estimator[PerceptronModel]

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    Definition Classes
    Model
  79. def save(path: String): Unit

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    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  80. def set[T](feature: StructFeature[T], value: T): PerceptronModel.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  81. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): PerceptronModel.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  82. def set[T](feature: SetFeature[T], value: Set[T]): PerceptronModel.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  83. def set[T](feature: ArrayFeature[T], value: Array[T]): PerceptronModel.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  84. final def set(paramPair: ParamPair[_]): PerceptronModel.this.type

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

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

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    Definition Classes
    Params
  87. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): PerceptronModel.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  88. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): PerceptronModel.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  89. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): PerceptronModel.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  90. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): PerceptronModel.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  91. final def setDefault(paramPairs: ParamPair[_]*): PerceptronModel.this.type

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

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    Attributes
    protected
    Definition Classes
    Params
  93. final def setInputCols(value: String*): PerceptronModel.this.type

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    Definition Classes
    HasInputAnnotationCols
  94. final def setInputCols(value: Array[String]): PerceptronModel.this.type

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    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  95. def setLazyAnnotator(value: Boolean): PerceptronModel.this.type

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    Definition Classes
    CanBeLazy
  96. def setModel(targetModel: AveragedPerceptron): PerceptronModel.this.type

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  97. final def setOutputCol(value: String): PerceptronModel.this.type

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    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  98. def setParent(parent: Estimator[PerceptronModel]): PerceptronModel

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

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    Definition Classes
    AnyRef
  100. def tag(tokenizedSentences: Array[TokenizedSentence]): Array[TaggedSentence]

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    Tags a group of sentences into POS tagged sentences The logic here is to create a sentence context, run through every word and evaluate its context Based on how frequent a context appears around a word, such context is given a score which is used to predict Some words are marked as non ambiguous from the beginning

    Tags a group of sentences into POS tagged sentences The logic here is to create a sentence context, run through every word and evaluate its context Based on how frequent a context appears around a word, such context is given a score which is used to predict Some words are marked as non ambiguous from the beginning

    tokenizedSentences

    Sentence in the form of single word tokens

    returns

    A list of sentences which have every word tagged

  101. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any
  102. final def transform(dataset: Dataset[_]): DataFrame

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    Given requirements are met, this applies ML transformation within a Pipeline or stand-alone Output annotation will be generated as a new column, previous annotations are still available separately metadata is built at schema level to record annotations structural information outside its content

    Given requirements are met, this applies ML transformation within a Pipeline or stand-alone Output annotation will be generated as a new column, previous annotations are still available separately metadata is built at schema level to record annotations structural information outside its content

    dataset

    Dataset[Row]

    Definition Classes
    AnnotatorModel → Transformer
  103. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  104. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  105. final def transformSchema(schema: StructType): StructType

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    requirement for pipeline transformation validation.

    requirement for pipeline transformation validation. It is called on fit()

    Definition Classes
    RawAnnotator → PipelineStage
  106. def transformSchema(schema: StructType, logging: Boolean): StructType

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

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    Internal constructor requirement for serialization of params

    Internal constructor requirement for serialization of params

    Definition Classes
    PerceptronModel → Identifiable
  108. def validate(schema: StructType): Boolean

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    takes a Dataset and checks to see if all the required annotation types are present.

    takes a Dataset and checks to see if all the required annotation types are present.

    schema

    to be validated

    returns

    True if all the required types are present, else false

    Attributes
    protected
    Definition Classes
    RawAnnotator
  109. final def wait(): Unit

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

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  112. def wrapColumnMetadata(col: Column): Column

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    Attributes
    protected
    Definition Classes
    RawAnnotator
  113. def write: MLWriter

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    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable

Inherited from PerceptronUtils

Inherited from CanBeLazy

Inherited from RawAnnotator[PerceptronModel]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[PerceptronModel]

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

Annotator types

Required input and expected output annotator types

Members

Parameter setters

Parameter getters