Packages

class SymmetricDeleteApproach extends AnnotatorApproach[SymmetricDeleteModel] with SymmetricDeleteParams

Trains a Symmetric Delete spelling correction algorithm. Retrieves tokens and utilizes distance metrics to compute possible derived words.

Inspired by SymSpell.

For instantiated/pretrained models, see SymmetricDeleteModel.

See SymmetricDeleteModelTestSpec for further reference.

Example

In this example, the dictionary "words.txt" has the form of

...
gummy
gummic
gummier
gummiest
gummiferous
...

This dictionary is then set to be the basis of the spell checker.

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

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

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

val spellChecker = new SymmetricDeleteApproach()
  .setInputCols("token")
  .setOutputCol("spell")
  .setDictionary("src/test/resources/spell/words.txt")

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

val pipelineModel = pipeline.fit(trainingData)
See also

NorvigSweetingApproach for an alternative approach to spell checking

ContextSpellCheckerApproach for a DL based approach

Linear Supertypes
SymmetricDeleteParams, AnnotatorApproach[SymmetricDeleteModel], CanBeLazy, DefaultParamsWritable, MLWritable, HasOutputAnnotatorType, HasOutputAnnotationCol, HasInputAnnotationCols, Estimator[SymmetricDeleteModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. SymmetricDeleteApproach
  2. SymmetricDeleteParams
  3. AnnotatorApproach
  4. CanBeLazy
  5. DefaultParamsWritable
  6. MLWritable
  7. HasOutputAnnotatorType
  8. HasOutputAnnotationCol
  9. HasInputAnnotationCols
  10. Estimator
  11. PipelineStage
  12. Logging
  13. Params
  14. Serializable
  15. Serializable
  16. Identifiable
  17. AnyRef
  18. Any
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Visibility
  1. Public
  2. All

Instance Constructors

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

Type Members

  1. type AnnotatorType = String
    Definition Classes
    HasOutputAnnotatorType

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. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  5. def _fit(dataset: Dataset[_], recursiveStages: Option[PipelineModel]): SymmetricDeleteModel
    Attributes
    protected
    Definition Classes
    AnnotatorApproach
  6. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  7. def beforeTraining(spark: SparkSession): Unit
    Definition Classes
    AnnotatorApproach
  8. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  9. final def clear(param: Param[_]): SymmetricDeleteApproach.this.type
    Definition Classes
    Params
  10. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  11. final def copy(extra: ParamMap): Estimator[SymmetricDeleteModel]
    Definition Classes
    AnnotatorApproach → Estimator → PipelineStage → Params
  12. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  13. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  14. 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
  15. def derivedWordDistances(wordFrequencies: List[(String, Long)], maxEditDistance: Int): Map[String, (List[String], Long)]

    Computes derived words from a frequency of words

  16. val description: String

    Spell checking algorithm inspired on Symmetric Delete algorithm

    Spell checking algorithm inspired on Symmetric Delete algorithm

    Definition Classes
    SymmetricDeleteApproachAnnotatorApproach
  17. val dictionary: ExternalResourceParam

    Optional dictionary of properly written words.

    Optional dictionary of properly written words. If provided, significantly boosts spell checking performance.

    Needs "tokenPattern" (Default: \S+) for parsing the resource.

    Example

    ...
    gummy
    gummic
    gummier
    gummiest
    gummiferous
    ...
  18. 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
  19. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  20. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  21. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  22. def explainParams(): String
    Definition Classes
    Params
  23. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  24. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  25. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  26. final def fit(dataset: Dataset[_]): SymmetricDeleteModel
    Definition Classes
    AnnotatorApproach → Estimator
  27. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[SymmetricDeleteModel]
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  28. def fit(dataset: Dataset[_], paramMap: ParamMap): SymmetricDeleteModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  29. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): SymmetricDeleteModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  30. 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
  31. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  32. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  33. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  34. def getDeletes(word: String, med: Int): List[String]

    Given a word, derive strings with up to maxEditDistance characters deleted

  35. 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
  36. 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
  37. 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
  38. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  39. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  40. 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
  41. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  42. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  43. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  44. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  45. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  46. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  47. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  48. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  49. val inputAnnotatorTypes: Array[AnnotatorType]

    Input annotator type : TOKEN

    Input annotator type : TOKEN

    Definition Classes
    SymmetricDeleteApproachHasInputAnnotationCols
  50. 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
  51. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  52. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  53. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  54. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  55. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  56. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  57. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  58. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  59. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  60. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  61. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  62. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  64. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  66. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. val longestWordLength: IntParam

    Length of longest word in corpus

    Length of longest word in corpus

    Definition Classes
    SymmetricDeleteParams
  69. 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
  70. val maxFrequency: LongParam

    Maximum frequency of a word in the corpus

    Maximum frequency of a word in the corpus

    Definition Classes
    SymmetricDeleteParams
  71. val minFrequency: LongParam

    Minimum frequency of a word in the corpus

    Minimum frequency of a word in the corpus

    Definition Classes
    SymmetricDeleteParams
  72. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  73. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  74. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  75. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  76. def onTrained(model: SymmetricDeleteModel, spark: SparkSession): Unit
    Definition Classes
    AnnotatorApproach
  77. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  78. val outputAnnotatorType: AnnotatorType

    Output annotator type : TOKEN

    Output annotator type : TOKEN

    Definition Classes
    SymmetricDeleteApproachHasOutputAnnotatorType
  79. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  80. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  81. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  82. final def set(paramPair: ParamPair[_]): SymmetricDeleteApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  83. final def set(param: String, value: Any): SymmetricDeleteApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  84. final def set[T](param: Param[T], value: T): SymmetricDeleteApproach.this.type
    Definition Classes
    Params
  85. final def setDefault(paramPairs: ParamPair[_]*): SymmetricDeleteApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  86. final def setDefault[T](param: Param[T], value: T): SymmetricDeleteApproach.this.type
    Attributes
    protected
    Definition Classes
    Params
  87. def setDeletesThreshold(value: Int): SymmetricDeleteApproach.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
  88. def setDictionary(path: String, tokenPattern: String = "\\S+", readAs: Format = ReadAs.TEXT, options: Map[String, String] = Map("format" -> "text")): SymmetricDeleteApproach.this.type

    Path to file with properly spelled words, tokenPattern is the regex pattern to identify them in text, readAs can be ReadAs.TEXT or ReadAs.SPARK, with options passed to Spark reader if the latter is set.

    Path to file with properly spelled words, tokenPattern is the regex pattern to identify them in text, readAs can be ReadAs.TEXT or ReadAs.SPARK, with options passed to Spark reader if the latter is set. Dictionary needs tokenPattern regex for separating words.

  89. def setDictionary(value: ExternalResource): SymmetricDeleteApproach.this.type

    External dictionary already in the form of ExternalResource, for which the Map member options has an entry defined for "tokenPattern".

    External dictionary already in the form of ExternalResource, for which the Map member options has an entry defined for "tokenPattern".

    Example

    val resource = ExternalResource(
      "src/test/resources/spell/words.txt",
      ReadAs.TEXT,
      Map("tokenPattern" -> "\\S+")
    )
    val spellChecker = new SymmetricDeleteApproach()
      .setInputCols("token")
      .setOutputCol("spell")
      .setDictionary(resource)
  90. def setDupsLimit(value: Int): SymmetricDeleteApproach.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
  91. def setFrequencyThreshold(value: Int): SymmetricDeleteApproach.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
  92. final def setInputCols(value: String*): SymmetricDeleteApproach.this.type
    Definition Classes
    HasInputAnnotationCols
  93. final def setInputCols(value: Array[String]): SymmetricDeleteApproach.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  94. def setLazyAnnotator(value: Boolean): SymmetricDeleteApproach.this.type
    Definition Classes
    CanBeLazy
  95. def setLongestWordLength(value: Int): SymmetricDeleteApproach.this.type

    Length of longest word in corpus

    Length of longest word in corpus

    Definition Classes
    SymmetricDeleteParams
  96. def setMaxEditDistance(value: Int): SymmetricDeleteApproach.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
  97. def setMaxFrequency(value: Long): SymmetricDeleteApproach.this.type

    Maximum frequency of a word in the corpus

    Maximum frequency of a word in the corpus

    Definition Classes
    SymmetricDeleteParams
  98. def setMinFrequency(value: Long): SymmetricDeleteApproach.this.type

    Minimum frequency of a word in the corpus

    Minimum frequency of a word in the corpus

    Definition Classes
    SymmetricDeleteParams
  99. final def setOutputCol(value: String): SymmetricDeleteApproach.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  100. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  101. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  102. def train(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): SymmetricDeleteModel
  103. final def transformSchema(schema: StructType): StructType

    requirement for pipeline transformation validation.

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

    Definition Classes
    AnnotatorApproach → PipelineStage
  104. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  105. val uid: String
    Definition Classes
    SymmetricDeleteApproach → Identifiable
  106. 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
    AnnotatorApproach
  107. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  108. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  109. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  110. def write: MLWriter
    Definition Classes
    DefaultParamsWritable → MLWritable

Inherited from SymmetricDeleteParams

Inherited from CanBeLazy

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from HasOutputAnnotatorType

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from Estimator[SymmetricDeleteModel]

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