Packages

class NormalizerModel extends AnnotatorModel[NormalizerModel] with HasSimpleAnnotate[NormalizerModel]

Instantiated Model of the Normalizer. For usage and examples, please see the documentation of that class.

See also

Normalizer for the base class

Linear Supertypes
HasSimpleAnnotate[NormalizerModel], AnnotatorModel[NormalizerModel], CanBeLazy, RawAnnotator[NormalizerModel], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[NormalizerModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. NormalizerModel
  2. HasSimpleAnnotate
  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 NormalizerModel()
  2. new NormalizerModel(uid: String)

    uid

    required internal uid for saving annotator

Type Members

  1. type AnnotationContent = Seq[Row]

    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
    Definition Classes
    HasOutputAnnotatorType
  3. case class TokenizerAndNormalizerMap(beginTokenizer: Int, endTokenizer: Int, token: String, beginNormalizer: Int, endNormalizer: Int, normalizer: String) extends Product with Serializable

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. def $$[T](feature: StructFeature[T]): T
    Attributes
    protected
    Definition Classes
    HasFeatures
  5. def $$[K, V](feature: MapFeature[K, V]): Map[K, V]
    Attributes
    protected
    Definition Classes
    HasFeatures
  6. def $$[T](feature: SetFeature[T]): Set[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  7. def $$[T](feature: ArrayFeature[T]): Array[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  8. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  9. def _transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  10. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  11. def annotate(annotations: Seq[Annotation]): Seq[Annotation]

    ToDo: Review implementation, Current implementation generates spaces between non-words, potentially breaking tokens

    ToDo: Review implementation, Current implementation generates spaces between non-words, potentially breaking tokens

    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
    NormalizerModel → HasSimpleAnnotate
  12. def applyRegexPatterns(word: String): String
  13. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  14. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  15. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  16. val cleanupPatterns: StringArrayParam

    normalization regex patterns which match will be removed from token

  17. final def clear(param: Param[_]): NormalizerModel.this.type
    Definition Classes
    Params
  18. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  19. def copy(extra: ParamMap): NormalizerModel

    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  20. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  21. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  22. def dfAnnotate: UserDefinedFunction

    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

    Definition Classes
    HasSimpleAnnotate
  23. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  24. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  25. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  26. def explainParams(): String
    Definition Classes
    Params
  27. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  28. def extraValidateMsg: String

    Override for additional custom schema checks

    Override for additional custom schema checks

    Attributes
    protected
    Definition Classes
    RawAnnotator
  29. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  30. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  31. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  32. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  33. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  34. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  35. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  36. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  37. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  38. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  39. def getCleanupPatterns: Array[String]

  40. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  41. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  42. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  43. def getLowercase: Boolean

  44. def getMaxLength: Int

  45. def getMinLength: Int

  46. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  47. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  48. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  49. def getSlangDict: Map[String, String]

    Txt file with delimited words to be transformed into something else

    Txt file with delimited words to be transformed into something else

    Attributes
    protected
  50. def getSlangMatchCase: Boolean

  51. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  52. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  53. def hasParent: Boolean
    Definition Classes
    Model
  54. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  55. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  56. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  57. val inputAnnotatorTypes: Array[AnnotatorType]

    Input annotator type : TOKEN

    Input annotator type : TOKEN

    Definition Classes
    NormalizerModel → HasInputAnnotationCols
  58. final val inputCols: StringArrayParam

    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
  59. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  60. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  61. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  62. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  63. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  64. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  65. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  66. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  69. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  71. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  72. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  75. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  76. val lowercase: BooleanParam

    whether to convert strings to lowercase

  77. val maxLength: IntParam

    Set the maximum allowed length for each token

  78. val minLength: IntParam

    Set the minimum allowed length for each token

  79. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  80. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  81. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  82. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  83. def onWrite(path: String, spark: SparkSession): Unit
    Attributes
    protected
    Definition Classes
    ParamsAndFeaturesWritable
  84. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  85. val outputAnnotatorType: AnnotatorType

    Output annotator type : TOKEN

    Output annotator type : TOKEN

    Definition Classes
    NormalizerModel → HasOutputAnnotatorType
  86. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  87. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  88. var parent: Estimator[NormalizerModel]
    Definition Classes
    Model
  89. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  90. def set[T](feature: StructFeature[T], value: T): NormalizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  91. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): NormalizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  92. def set[T](feature: SetFeature[T], value: Set[T]): NormalizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  93. def set[T](feature: ArrayFeature[T], value: Array[T]): NormalizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  94. final def set(paramPair: ParamPair[_]): NormalizerModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  95. final def set(param: String, value: Any): NormalizerModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  96. final def set[T](param: Param[T], value: T): NormalizerModel.this.type
    Definition Classes
    Params
  97. def setCleanupPatterns(value: Array[String]): NormalizerModel.this.type

  98. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): NormalizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  99. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): NormalizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  100. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): NormalizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  101. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): NormalizerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  102. final def setDefault(paramPairs: ParamPair[_]*): NormalizerModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  103. final def setDefault[T](param: Param[T], value: T): NormalizerModel.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  104. final def setInputCols(value: String*): NormalizerModel.this.type
    Definition Classes
    HasInputAnnotationCols
  105. def setInputCols(value: Array[String]): NormalizerModel.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  106. def setLazyAnnotator(value: Boolean): NormalizerModel.this.type
    Definition Classes
    CanBeLazy
  107. def setLowercase(value: Boolean): NormalizerModel.this.type

  108. def setMaxLength(value: Int): NormalizerModel.this.type

  109. def setMinLength(value: Int): NormalizerModel.this.type

  110. final def setOutputCol(value: String): NormalizerModel.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  111. def setParent(parent: Estimator[NormalizerModel]): NormalizerModel
    Definition Classes
    Model
  112. def setSlangDict(value: Map[String, String]): NormalizerModel.this.type

  113. def setSlangMatchCase(value: Boolean): NormalizerModel.this.type

  114. val slangDict: MapFeature[String, String]

    slangDict

    slangDict

    Attributes
    protected
  115. val slangMatchCase: BooleanParam

    whether or not to be case sensitive to match slangs.

    whether or not to be case sensitive to match slangs. Defaults to false.

  116. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  117. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  118. final def transform(dataset: Dataset[_]): DataFrame

    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
  119. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  120. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  121. final def transformSchema(schema: StructType): StructType

    requirement for pipeline transformation validation.

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

    Definition Classes
    RawAnnotator → PipelineStage
  122. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  123. val uid: String
    Definition Classes
    NormalizerModel → Identifiable
  124. def validate(schema: StructType): Boolean

    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
  125. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  126. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  127. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  128. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  129. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable

Inherited from HasSimpleAnnotate[NormalizerModel]

Inherited from AnnotatorModel[NormalizerModel]

Inherited from CanBeLazy

Inherited from RawAnnotator[NormalizerModel]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[NormalizerModel]

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 annotator can take. Users can set and get the parameter values through setters and getters, respectively.

Annotator types

Required input and expected output annotator types

Members

Parameter setters

Parameter getters