Packages

class ContextSpellCheckerModel extends AnnotatorModel[ContextSpellCheckerModel] with HasSimpleAnnotate[ContextSpellCheckerModel] with WeightedLevenshtein with WriteTensorflowModel with ParamsAndFeaturesWritable with HasTransducerFeatures

Implements a deep-learning based Noisy Channel Model Spell Algorithm. Correction candidates are extracted combining context information and word information.

Spell Checking is a sequence to sequence mapping problem. Given an input sequence, potentially containing a certain number of errors, ContextSpellChecker will rank correction sequences according to three things:

  1. Different correction candidates for each word — word level.
  2. The surrounding text of each word, i.e. it’s context — sentence level.
  3. The relative cost of different correction candidates according to the edit operations at the character level it requires — subword level.

For an in-depth explanation of the module see the article Applying Context Aware Spell Checking in Spark NLP.

This is the instantiated model of the ContextSpellCheckerApproach. For training your own model, please see the documentation of that class.

Pretrained models can be loaded with pretrained of the companion object:

val spellChecker = ContextSpellCheckerModel.pretrained()
  .setInputCols("token")
  .setOutputCol("checked")

The default model is "spellcheck_dl", if no name is provided. For available pretrained models please see the Models Hub.

For extended examples of usage, see the Spark NLP Workshop and the ContextSpellCheckerTestSpec.

Example

import spark.implicits._
import com.johnsnowlabs.nlp.DocumentAssembler
import com.johnsnowlabs.nlp.annotators.Tokenizer
import com.johnsnowlabs.nlp.annotators.spell.context.ContextSpellCheckerModel
import org.apache.spark.ml.Pipeline

val documentAssembler = new DocumentAssembler()
  .setInputCol("text")
  .setOutputCol("doc")

val tokenizer = new Tokenizer()
  .setInputCols(Array("doc"))
  .setOutputCol("token")

val spellChecker = ContextSpellCheckerModel
  .pretrained()
  .setTradeOff(12.0f)
  .setInputCols("token")
  .setOutputCol("checked")

val pipeline = new Pipeline().setStages(Array(
  documentAssembler,
  tokenizer,
  spellChecker
))

val data = Seq("It was a cold , dreary day and the country was white with smow .").toDF("text")
val result = pipeline.fit(data).transform(data)

result.select("checked.result").show(false)
+--------------------------------------------------------------------------------+
|result                                                                          |
+--------------------------------------------------------------------------------+
|[It, was, a, cold, ,, dreary, day, and, the, country, was, white, with, snow, .]|
+--------------------------------------------------------------------------------+
See also

NorvigSweetingModel and SymmetricDeleteModel for alternative approaches to spell checking

Ordering
  1. Grouped
  2. Alphabetic
  3. By Inheritance
Inherited
  1. ContextSpellCheckerModel
  2. HasTransducerFeatures
  3. WriteTensorflowModel
  4. WeightedLevenshtein
  5. HasSimpleAnnotate
  6. AnnotatorModel
  7. CanBeLazy
  8. RawAnnotator
  9. HasOutputAnnotationCol
  10. HasInputAnnotationCols
  11. HasOutputAnnotatorType
  12. ParamsAndFeaturesWritable
  13. HasFeatures
  14. DefaultParamsWritable
  15. MLWritable
  16. Model
  17. Transformer
  18. PipelineStage
  19. Logging
  20. Params
  21. Serializable
  22. Serializable
  23. Identifiable
  24. AnyRef
  25. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new ContextSpellCheckerModel()

    Annotator reference id.

    Annotator reference id. Used to identify elements in metadata or to refer to this annotator type

  2. new ContextSpellCheckerModel(uid: String)

    uid

    required uid for storing annotator to disk

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. implicit class StringTools extends AnyRef

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 $$(feature: TransducerSeqFeature): Seq[SpecialClassParser]
    Attributes
    protected
    Definition Classes
    HasTransducerFeatures
  5. def $$(feature: TransducerFeature): VocabParser
    Attributes
    protected
    Definition Classes
    HasTransducerFeatures
  6. def $$[T](feature: StructFeature[T]): T
    Attributes
    protected
    Definition Classes
    HasFeatures
  7. def $$[K, V](feature: MapFeature[K, V]): Map[K, V]
    Attributes
    protected
    Definition Classes
    HasFeatures
  8. def $$[T](feature: SetFeature[T]): Set[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  9. def $$[T](feature: ArrayFeature[T]): Array[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  10. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  11. def _transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  12. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  13. def annotate(annotations: Seq[Annotation]): Seq[Annotation]

    takes a document and annotations and produces new annotations of this annotator's annotation type

    takes a document and annotations and produces new annotations of this annotator's annotation type

    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
    ContextSpellCheckerModelHasSimpleAnnotate
  14. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  15. def backTrack(dist: Array[Array[Float]], s2: String, s1: String, j: Int, i: Int, acc: Seq[(String, String)]): Seq[(String, String)]
    Definition Classes
    WeightedLevenshtein
  16. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
  17. val caseStrategy: IntParam

    What case combinations to try when generating candidates (Default: CandidateStrategy.ALL).

  18. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  19. val classes: MapFeature[Int, (Int, Int)]

    Classes the spell checker recognizes

  20. final def clear(param: Param[_]): ContextSpellCheckerModel.this.type
    Definition Classes
    Params
  21. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  22. val compareLowcase: BooleanParam

    If true will compare tokens in low case with vocabulary (Default: false)

  23. def computeMask(annotations: Seq[Annotation]): Array[Boolean]
  24. def computeTrellis(annotations: Seq[Annotation], mask: Seq[Boolean]): Array[Array[(String, Double, String)]]
  25. val configProtoBytes: IntArrayParam

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString()

  26. def copy(extra: ParamMap): ContextSpellCheckerModel

    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  27. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  28. val correctSymbols: BooleanParam

    Whether to correct special symbols or skip spell checking for them

  29. def decodeViterbi(trellis: Array[Array[(String, Double, String)]]): (Array[String], Double)
  30. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  31. 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
  32. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  33. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  34. val errorThreshold: FloatParam

    Threshold perplexity for a word to be considered as an error.

  35. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  36. def explainParams(): String
    Definition Classes
    Params
  37. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  38. def extraValidateMsg: String

    Override for additional custom schema checks

    Override for additional custom schema checks

    Attributes
    protected
    Definition Classes
    RawAnnotator
  39. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  40. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  41. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  42. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  43. val gamma: FloatParam

    Controls the influence of individual word frequency in the decision (Default: 120.0f).

  44. def get(feature: TransducerSeqFeature): Option[Seq[SpecialClassParser]]
    Attributes
    protected
    Definition Classes
    HasTransducerFeatures
  45. def get(feature: TransducerFeature): Option[VocabParser]
    Attributes
    protected
    Definition Classes
    HasTransducerFeatures
  46. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  47. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  48. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  49. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  50. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  51. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  52. def getClassCandidates(transducer: ITransducer[Candidate], token: String, label: String, maxDist: Int, limit: Int = 2): Seq[(String, String, Float)]
  53. def getConfigProtoBytes: Option[Array[Byte]]

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

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  56. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  57. def getModelIfNotSet: TensorflowSpell
  58. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  59. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  60. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  61. def getVocabCandidates(token: String, maxDist: Int): List[(String, String, Float)]
  62. def getWordClasses(): Seq[(String, String)]

  63. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  64. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  65. def hasParent: Boolean
    Definition Classes
    Model
  66. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  67. val idsVocab: MapFeature[Int, String]

    Mapping of ids to vocabulary

  68. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  69. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. val inputAnnotatorTypes: Array[String]

    Input Annotator Types: TOKEN

    Input Annotator Types: TOKEN

    Definition Classes
    ContextSpellCheckerModelHasInputAnnotationCols
  71. 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
  72. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  73. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  74. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  75. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  76. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  77. def learnDist(s1: String, s2: String): Seq[(String, String)]
    Definition Classes
    WeightedLevenshtein
  78. def levenshteinDist(s11: String, s22: String)(cost: (String, String) ⇒ Float): Float
    Definition Classes
    WeightedLevenshtein
  79. def loadWeights(filename: String): Map[String, Map[String, Float]]
    Definition Classes
    WeightedLevenshtein
  80. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  81. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  82. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  83. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  84. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  85. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  86. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  87. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  88. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  89. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  90. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  91. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  92. val maxCandidates: IntParam

    Maximum number of candidates for every word (Default: 6).

  93. val maxWindowLen: IntParam

    Maximum size for the window used to remember history prior to every correction (Default: 5).

  94. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  95. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  96. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  97. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  98. def onWrite(path: String, spark: SparkSession): Unit
  99. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  100. val outputAnnotatorType: AnnotatorType

    Output Annotator Types: TOKEN

    Output Annotator Types: TOKEN

    Definition Classes
    ContextSpellCheckerModelHasOutputAnnotatorType
  101. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  102. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  103. var parent: Estimator[ContextSpellCheckerModel]
    Definition Classes
    Model
  104. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  105. def set(feature: TransducerSeqFeature, value: Seq[SpecialClassParser]): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    HasTransducerFeatures
  106. def set(feature: TransducerFeature, value: VocabParser): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    HasTransducerFeatures
  107. def set[T](feature: StructFeature[T], value: T): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  108. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  109. def set[T](feature: SetFeature[T], value: Set[T]): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  110. def set[T](feature: ArrayFeature[T], value: Array[T]): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  111. final def set(paramPair: ParamPair[_]): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  112. final def set(param: String, value: Any): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  113. final def set[T](param: Param[T], value: T): ContextSpellCheckerModel.this.type
    Definition Classes
    Params
  114. def setCaseStrategy(k: Int): ContextSpellCheckerModel.this.type

  115. def setClasses(c: Map[Int, (Int, Int)]): ContextSpellCheckerModel.this.type

  116. def setCompareLowcase(value: Boolean): ContextSpellCheckerModel.this.type

  117. def setConfigProtoBytes(bytes: Array[Int]): ContextSpellCheckerModel.this.type

  118. def setCorrectSymbols(value: Boolean): ContextSpellCheckerModel.this.type

  119. def setDefault(feature: TransducerSeqFeature, value: () ⇒ Seq[SpecialClassParser]): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    HasTransducerFeatures
  120. def setDefault(feature: TransducerFeature, value: () ⇒ VocabParser): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    HasTransducerFeatures
  121. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  122. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  123. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  124. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  125. final def setDefault(paramPairs: ParamPair[_]*): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  126. final def setDefault[T](param: Param[T], value: T): ContextSpellCheckerModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  127. def setErrorThreshold(t: Float): ContextSpellCheckerModel.this.type

  128. def setGamma(g: Float): ContextSpellCheckerModel.this.type

  129. final def setInputCols(value: String*): ContextSpellCheckerModel.this.type
    Definition Classes
    HasInputAnnotationCols
  130. final def setInputCols(value: Array[String]): ContextSpellCheckerModel.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  131. def setLazyAnnotator(value: Boolean): ContextSpellCheckerModel.this.type
    Definition Classes
    CanBeLazy
  132. def setMaxCandidates(k: Int): ContextSpellCheckerModel.this.type

  133. def setMaxWindowLen(w: Int): ContextSpellCheckerModel.this.type

  134. def setModelIfNotSet(spark: SparkSession, tensorflow: TensorflowWrapper): ContextSpellCheckerModel.this.type
  135. final def setOutputCol(value: String): ContextSpellCheckerModel.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  136. def setParent(parent: Estimator[ContextSpellCheckerModel]): ContextSpellCheckerModel
    Definition Classes
    Model
  137. def setSpecialClassesTransducers(transducers: Seq[SpecialClassParser]): ContextSpellCheckerModel.this.type

  138. def setTradeOff(lambda: Float): ContextSpellCheckerModel.this.type

  139. def setUseNewLines(useIt: Boolean): ContextSpellCheckerModel.this.type

  140. def setVocabFreq(v: Map[String, Double]): ContextSpellCheckerModel.this.type

  141. def setVocabIds(v: Map[String, Int]): ContextSpellCheckerModel.this.type

  142. def setVocabTransducer(trans: ITransducer[Candidate]): ContextSpellCheckerModel.this.type

  143. def setWeights(w: HashMap[String, HashMap[String, Double]]): ContextSpellCheckerModel.this.type

  144. def setWeights(w: Map[String, Map[String, Float]]): ContextSpellCheckerModel.this.type

  145. def setWordMaxDistance(k: Int): ContextSpellCheckerModel.this.type

  146. val specialTransducers: TransducerSeqFeature
  147. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  148. def toOption(boolean: Boolean): Option[Boolean]
  149. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  150. val tradeoff: FloatParam

    Tradeoff between the cost of a word and a transition in the language model (Default: 18.0f).

  151. val transducer: TransducerFeature
  152. 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
  153. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  154. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  155. 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
  156. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  157. val uid: String
    Definition Classes
    ContextSpellCheckerModel → Identifiable
  158. def updateRegexClass(label: String, regex: String): ContextSpellCheckerModel
  159. def updateVocabClass(label: String, vocabList: ArrayList[String], append: Boolean = true): ContextSpellCheckerModel
  160. val useNewLines: BooleanParam

    When set to true new lines will be treated as any other character (Default: false).

    When set to true new lines will be treated as any other character (Default: false). When set to false correction is applied on paragraphs as defined by newline characters.

  161. 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
  162. val vocabFreq: MapFeature[String, Double]

    Frequency words from the vocabulary

  163. val vocabIds: MapFeature[String, Int]

    Mapping of vocabulary to ids

  164. def wLevenshteinDist(s1: String, s2: String, weights: Map[String, Map[String, Float]]): Float
    Definition Classes
    WeightedLevenshtein
  165. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  166. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  167. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  168. val weights: MapFeature[String, Map[String, Float]]
  169. val wordMaxDistance: IntParam

    Maximum distance for the generated candidates for every word, minimum 1.

  170. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  171. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
  172. def writeTensorflowHub(path: String, tfPath: String, spark: SparkSession, suffix: String = "_use"): Unit
    Definition Classes
    WriteTensorflowModel
  173. def writeTensorflowModel(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]] = None): Unit
    Definition Classes
    WriteTensorflowModel
  174. def writeTensorflowModelV2(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]] = None, savedSignatures: Option[Map[String, String]] = None): Unit
    Definition Classes
    WriteTensorflowModel

Inherited from HasTransducerFeatures

Inherited from WriteTensorflowModel

Inherited from WeightedLevenshtein

Inherited from CanBeLazy

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[ContextSpellCheckerModel]

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