Packages

class SymmetricDeleteModel extends AnnotatorModel[SymmetricDeleteModel] with HasSimpleAnnotate[SymmetricDeleteModel] with SymmetricDeleteParams

Symmetric Delete spelling correction algorithm.

The Symmetric Delete spelling correction algorithm reduces the complexity of edit candidate generation and dictionary lookup for a given Damerau-Levenshtein distance. It is six orders of magnitude faster (than the standard approach with deletes + transposes + replaces + inserts) and language independent.

Inspired by SymSpell.

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

val spell = SymmetricDeleteModel.pretrained()
  .setInputCols("token")
  .setOutputCol("spell")

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

See SymmetricDeleteModelTestSpec for further reference.

Example

import spark.implicits._
import com.johnsnowlabs.nlp.base.DocumentAssembler
import com.johnsnowlabs.nlp.annotators.Tokenizer
import com.johnsnowlabs.nlp.annotators.spell.symmetric.SymmetricDeleteModel
import org.apache.spark.ml.Pipeline

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

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

val spellChecker = SymmetricDeleteModel.pretrained()
  .setInputCols("token")
  .setOutputCol("spell")

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

val data = Seq("spmetimes i wrrite wordz erong.").toDF("text")
val result = pipeline.fit(data).transform(data)
result.select("spell.result").show(false)
+--------------------------------------+
|result                                |
+--------------------------------------+
|[sometimes, i, write, words, wrong, .]|
+--------------------------------------+
See also

NorvigSweetingModel for an alternative approach to spell checking

ContextSpellCheckerModel for a DL based approach

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

Instance Constructors

  1. new SymmetricDeleteModel()
  2. new SymmetricDeleteModel(uid: String)

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 SuggestedWord(correction: String, frequency: Long, distance: Int, score: Double) 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]

    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
    SymmetricDeleteModelHasSimpleAnnotate
  12. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  13. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  14. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  15. def checkSpellWord(originalWord: String): (String, Double)
  16. final def clear(param: Param[_]): SymmetricDeleteModel.this.type
    Definition Classes
    Params
  17. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  18. def copy(extra: ParamMap): SymmetricDeleteModel

    requirement for annotators copies

    requirement for annotators copies

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

    Minimum frequency of corrections a word needs to have to be considered from training.

    Minimum frequency of corrections a word needs to have to be considered from training. Increase if training set is LARGE (Default: 0).

    Definition Classes
    SymmetricDeleteParams
  22. val derivedWords: MapFeature[String, (List[String], Long)]
    Attributes
    protected
  23. 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
  24. val dictionary: MapFeature[String, Long]
    Attributes
    protected
  25. val dupsLimit: IntParam

    Maximum duplicate of characters in a word to consider (Default: 2).

    Maximum duplicate of characters in a word to consider (Default: 2).

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

    Override for additional custom schema checks

    Override for additional custom schema checks

    Attributes
    protected
    Definition Classes
    RawAnnotator
  32. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  33. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  34. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  35. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  36. val frequencyThreshold: IntParam

    Minimum frequency of words to be considered from training.

    Minimum frequency of words to be considered from training. Increase if training set is LARGE (Default: 0).

    Definition Classes
    SymmetricDeleteParams
  37. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  38. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  39. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  40. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  41. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  42. def getCaseWordType(word: String): Char
  43. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  44. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  45. def getDeletesThreshold: Int

    Minimum frequency of corrections a word needs to have to be considered from training.

    Minimum frequency of corrections a word needs to have to be considered from training. Increase if training set is LARGE (Default: 0).

    Definition Classes
    SymmetricDeleteParams
  46. def getDictionarySuggestions(word: String): Option[SuggestedWord]
  47. def getDupsLimit: Int

    Maximum duplicate of characters in a word to consider (Default: 2).

    Maximum duplicate of characters in a word to consider (Default: 2).

    Definition Classes
    SymmetricDeleteParams
  48. def getFrequencyThreshold: Int

    Minimum frequency of words to be considered from training.

    Minimum frequency of words to be considered from training. Increase if training set is LARGE (Default: 0).

    Definition Classes
    SymmetricDeleteParams
  49. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  50. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  51. def getMaxEditDistance: Int

    Max edit distance characters to derive strings from a word

    Max edit distance characters to derive strings from a word

    Definition Classes
    SymmetricDeleteParams
  52. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  53. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  54. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  55. def getScoreFrequency(word: String): Double
  56. def getSuggestedCorrections(word: String): Option[SuggestedWord]

    Return list of suggested corrections for potentially incorrectly spelled word

  57. def getSymmetricSuggestions(word: String): Option[SuggestedWord]
  58. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  59. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  60. def hasParent: Boolean
    Definition Classes
    Model
  61. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  62. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  63. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  64. val inputAnnotatorTypes: Array[AnnotatorType]

    Input annotator type: TOKEN

    Input annotator type: TOKEN

    Definition Classes
    SymmetricDeleteModelHasInputAnnotationCols
  65. 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
  66. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  67. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  68. def isNoisyWord(word: String): Boolean
  69. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  70. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  71. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  72. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  73. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  75. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  76. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  77. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  78. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  80. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  81. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  82. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  83. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  84. val longestWordLength: IntParam

    Length of longest word in corpus

    Length of longest word in corpus

    Definition Classes
    SymmetricDeleteParams
  85. val maxEditDistance: IntParam

    Max edit distance characters to derive strings from a word (Default: 3)

    Max edit distance characters to derive strings from a word (Default: 3)

    Definition Classes
    SymmetricDeleteParams
  86. val maxFrequency: LongParam

    Maximum frequency of a word in the corpus

    Maximum frequency of a word in the corpus

    Definition Classes
    SymmetricDeleteParams
  87. val minFrequency: LongParam

    Minimum frequency of a word in the corpus

    Minimum frequency of a word in the corpus

    Definition Classes
    SymmetricDeleteParams
  88. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  89. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  90. def normalizeFrequencyValue(value: Long): Double
  91. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  92. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  93. def onWrite(path: String, spark: SparkSession): Unit
    Attributes
    protected
    Definition Classes
    ParamsAndFeaturesWritable
  94. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  95. val outputAnnotatorType: AnnotatorType

    Output annotator type: TOKEN

    Output annotator type: TOKEN

    Definition Classes
    SymmetricDeleteModelHasOutputAnnotatorType
  96. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  97. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  98. var parent: Estimator[SymmetricDeleteModel]
    Definition Classes
    Model
  99. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  100. def set[T](feature: StructFeature[T], value: T): SymmetricDeleteModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  101. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): SymmetricDeleteModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  102. def set[T](feature: SetFeature[T], value: Set[T]): SymmetricDeleteModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  103. def set[T](feature: ArrayFeature[T], value: Array[T]): SymmetricDeleteModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  104. final def set(paramPair: ParamPair[_]): SymmetricDeleteModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  105. final def set(param: String, value: Any): SymmetricDeleteModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  106. final def set[T](param: Param[T], value: T): SymmetricDeleteModel.this.type
    Definition Classes
    Params
  107. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): SymmetricDeleteModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  108. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): SymmetricDeleteModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  109. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): SymmetricDeleteModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  110. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): SymmetricDeleteModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  111. final def setDefault(paramPairs: ParamPair[_]*): SymmetricDeleteModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  112. final def setDefault[T](param: Param[T], value: T): SymmetricDeleteModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  113. def setDeletesThreshold(value: Int): SymmetricDeleteModel.this.type

    Minimum frequency of corrections a word needs to have to be considered from training.

    Minimum frequency of corrections a word needs to have to be considered from training. Increase if training set is LARGE (Default: 0).

    Definition Classes
    SymmetricDeleteParams
  114. def setDerivedWords(value: Map[String, (List[String], Long)]): SymmetricDeleteModel.this.type

  115. def setDictionary(value: Map[String, Long]): SymmetricDeleteModel.this.type

  116. def setDupsLimit(value: Int): SymmetricDeleteModel.this.type

    Maximum duplicate of characters in a word to consider (Default: 2)

    Maximum duplicate of characters in a word to consider (Default: 2)

    Definition Classes
    SymmetricDeleteParams
  117. def setFrequencyThreshold(value: Int): SymmetricDeleteModel.this.type

    Minimum frequency of words to be considered from training.

    Minimum frequency of words to be considered from training. Increase if training set is LARGE (Default: 0)

    Definition Classes
    SymmetricDeleteParams
  118. final def setInputCols(value: String*): SymmetricDeleteModel.this.type
    Definition Classes
    HasInputAnnotationCols
  119. final def setInputCols(value: Array[String]): SymmetricDeleteModel.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  120. def setLazyAnnotator(value: Boolean): SymmetricDeleteModel.this.type
    Definition Classes
    CanBeLazy
  121. def setLongestWordLength(value: Int): SymmetricDeleteModel.this.type

    Length of longest word in corpus

    Length of longest word in corpus

    Definition Classes
    SymmetricDeleteParams
  122. def setMaxEditDistance(value: Int): SymmetricDeleteModel.this.type

    Max edit distance characters to derive strings from a word

    Max edit distance characters to derive strings from a word

    Definition Classes
    SymmetricDeleteParams
  123. def setMaxFrequency(value: Long): SymmetricDeleteModel.this.type

    Maximum frequency of a word in the corpus

    Maximum frequency of a word in the corpus

    Definition Classes
    SymmetricDeleteParams
  124. def setMinFrequency(value: Long): SymmetricDeleteModel.this.type

    Minimum frequency of a word in the corpus

    Minimum frequency of a word in the corpus

    Definition Classes
    SymmetricDeleteParams
  125. final def setOutputCol(value: String): SymmetricDeleteModel.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  126. def setParent(parent: Estimator[SymmetricDeleteModel]): SymmetricDeleteModel
    Definition Classes
    Model
  127. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  128. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  129. 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
  130. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  131. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  132. 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
  133. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  134. def transformToOriginalCaseType(caseType: Char, word: String): String
  135. val uid: String
    Definition Classes
    SymmetricDeleteModel → Identifiable
  136. 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
  137. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  138. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  139. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  140. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  141. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable

Inherited from SymmetricDeleteParams

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[SymmetricDeleteModel]

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