Packages

class WordEmbeddings extends AnnotatorApproach[WordEmbeddingsModel] with HasStorage with HasEmbeddingsProperties

Word Embeddings lookup annotator that maps tokens to vectors.

For instantiated/pretrained models, see WordEmbeddingsModel.

A custom token lookup dictionary for embeddings can be set with setStoragePath. Each line of the provided file needs to have a token, followed by their vector representation, delimited by a spaces.

...
are 0.39658191506190343 0.630968081620067 0.5393722253731201 0.8428180123359783
were 0.7535235923631415 0.9699218875629833 0.10397182122983872 0.11833962569383116
stress 0.0492683418305907 0.9415954572751959 0.47624463167525755 0.16790967216778263
induced 0.1535748762292387 0.33498936903209897 0.9235178224122094 0.1158772920395934
...

If a token is not found in the dictionary, then the result will be a zero vector of the same dimension. Statistics about the rate of converted tokens, can be retrieved with WordEmbeddingsModel.withCoverageColumn and WordEmbeddingsModel.overallCoverage.

For extended examples of usage, see the Examples and the WordEmbeddingsTestSpec.

Example

In this example, the file random_embeddings_dim4.txt has the form of the content above.

import spark.implicits._
import com.johnsnowlabs.nlp.base.DocumentAssembler
import com.johnsnowlabs.nlp.annotators.Tokenizer
import com.johnsnowlabs.nlp.embeddings.WordEmbeddings
import com.johnsnowlabs.nlp.util.io.ReadAs
import com.johnsnowlabs.nlp.EmbeddingsFinisher
import org.apache.spark.ml.Pipeline

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

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

val embeddings = new WordEmbeddings()
  .setStoragePath("src/test/resources/random_embeddings_dim4.txt", ReadAs.TEXT)
  .setStorageRef("glove_4d")
  .setDimension(4)
  .setInputCols("document", "token")
  .setOutputCol("embeddings")

val embeddingsFinisher = new EmbeddingsFinisher()
  .setInputCols("embeddings")
  .setOutputCols("finished_embeddings")
  .setOutputAsVector(true)
  .setCleanAnnotations(false)

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

val data = Seq("The patient was diagnosed with diabetes.").toDF("text")
val result = pipeline.fit(data).transform(data)

result.selectExpr("explode(finished_embeddings) as result").show(false)
+----------------------------------------------------------------------------------+
|result                                                                            |
+----------------------------------------------------------------------------------+
|[0.9439099431037903,0.4707513153553009,0.806300163269043,0.16176554560661316]     |
|[0.7966810464859009,0.5551124811172485,0.8861005902290344,0.28284206986427307]    |
|[0.025029370561242104,0.35177749395370483,0.052506182342767715,0.1887107789516449]|
|[0.08617766946554184,0.8399239182472229,0.5395117998123169,0.7864698767662048]    |
|[0.6599600911140442,0.16109347343444824,0.6041093468666077,0.8913561105728149]    |
|[0.5955275893211365,0.01899011991918087,0.4397728443145752,0.8911281824111938]    |
|[0.9840458631515503,0.7599489092826843,0.9417727589607239,0.8624503016471863]     |
+----------------------------------------------------------------------------------+
See also

SentenceEmbeddings to combine embeddings into a sentence-level representation

Annotators Main Page for a list of transformer based embeddings

Linear Supertypes
HasEmbeddingsProperties, HasProtectedParams, HasStorage, HasCaseSensitiveProperties, HasStorageOptions, HasStorageRef, ParamsAndFeaturesWritable, HasFeatures, AnnotatorApproach[WordEmbeddingsModel], CanBeLazy, DefaultParamsWritable, MLWritable, HasOutputAnnotatorType, HasOutputAnnotationCol, HasInputAnnotationCols, Estimator[WordEmbeddingsModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. WordEmbeddings
  2. HasEmbeddingsProperties
  3. HasProtectedParams
  4. HasStorage
  5. HasCaseSensitiveProperties
  6. HasStorageOptions
  7. HasStorageRef
  8. ParamsAndFeaturesWritable
  9. HasFeatures
  10. AnnotatorApproach
  11. CanBeLazy
  12. DefaultParamsWritable
  13. MLWritable
  14. HasOutputAnnotatorType
  15. HasOutputAnnotationCol
  16. HasInputAnnotationCols
  17. Estimator
  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 WordEmbeddings()

    Annotator reference id.

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

  2. new WordEmbeddings(uid: String)

    uid

    required uid for storing annotator to disk

Type Members

  1. implicit class ProtectedParam[T] extends Param[T]
    Definition Classes
    HasProtectedParams
  2. 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. 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 _fit(dataset: Dataset[_], recursiveStages: Option[PipelineModel]): WordEmbeddingsModel
    Attributes
    protected
    Definition Classes
    AnnotatorApproach
  10. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  11. def beforeTraining(spark: SparkSession): Unit
    Definition Classes
    AnnotatorApproach
  12. val caseSensitive: BooleanParam

    Whether to ignore case in index lookups (Default depends on model)

    Whether to ignore case in index lookups (Default depends on model)

    Definition Classes
    HasCaseSensitiveProperties
  13. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  14. final def clear(param: Param[_]): WordEmbeddings.this.type
    Definition Classes
    Params
  15. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  16. final def copy(extra: ParamMap): Estimator[WordEmbeddingsModel]
    Definition Classes
    AnnotatorApproach → Estimator → PipelineStage → Params
  17. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  18. def createDatabaseConnection(database: Name): RocksDBConnection
    Definition Classes
    HasStorageRef
  19. def createWriter(database: Name, connection: RocksDBConnection): StorageWriter[_]
    Attributes
    protected
    Definition Classes
    WordEmbeddings → HasStorage
  20. val databases: Array[Name]
    Definition Classes
    WordEmbeddings → HasStorage
  21. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  22. val description: String

    Word Embeddings lookup annotator that maps tokens to vectors

    Word Embeddings lookup annotator that maps tokens to vectors

    Definition Classes
    WordEmbeddings → AnnotatorApproach
  23. val dimension: ProtectedParam[Int]

    Number of embedding dimensions (Default depends on model)

    Number of embedding dimensions (Default depends on model)

    Definition Classes
    HasEmbeddingsProperties
  24. val enableInMemoryStorage: BooleanParam
    Definition Classes
    HasStorageOptions
  25. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  26. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  27. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  28. def explainParams(): String
    Definition Classes
    Params
  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. final def fit(dataset: Dataset[_]): WordEmbeddingsModel
    Definition Classes
    AnnotatorApproach → Estimator
  34. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[WordEmbeddingsModel]
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  35. def fit(dataset: Dataset[_], paramMap: ParamMap): WordEmbeddingsModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  36. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): WordEmbeddingsModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  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 getCaseSensitive: Boolean

    Definition Classes
    HasCaseSensitiveProperties
  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 getDimension: Int

    Definition Classes
    HasEmbeddingsProperties
  46. def getEnableInMemoryStorage: Boolean
    Definition Classes
    HasStorageOptions
  47. def getIncludeStorage: Boolean
    Definition Classes
    HasStorageOptions
  48. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  49. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  50. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  51. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  52. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  53. def getStoragePath: Option[ExternalResource]

    Definition Classes
    HasStorage
  54. def getStorageRef: String
    Definition Classes
    HasStorageRef
  55. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  56. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  57. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  58. val includeStorage: BooleanParam
    Definition Classes
    HasStorageOptions
  59. def index(fitDataset: Dataset[_], storageSourcePath: Option[String], readAs: Option[util.io.ReadAs.Value], writers: Map[Name, StorageWriter[_]], readOptions: Option[Map[String, String]]): Unit
    Attributes
    protected
    Definition Classes
    WordEmbeddings → HasStorage
  60. def indexStorage(fitDataset: Dataset[_], resource: Option[ExternalResource]): Unit
    Definition Classes
    HasStorage
  61. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  62. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. val inputAnnotatorTypes: Array[String]

    Input annotation type : DOCUMENT, TOKEN

    Input annotation type : DOCUMENT, TOKEN

    Definition Classes
    WordEmbeddings → HasInputAnnotationCols
  64. 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
  65. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  66. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  67. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  68. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  69. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  70. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  71. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  75. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  76. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  77. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  78. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  80. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  81. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  82. val missingRefMsg: String

    Error message

    Error message

    Attributes
    protected
    Definition Classes
    WordEmbeddings → HasStorage
  83. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  84. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  85. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  86. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  87. def onTrained(model: WordEmbeddingsModel, spark: SparkSession): Unit
    Definition Classes
    AnnotatorApproach
  88. def onWrite(path: String, spark: SparkSession): Unit
    Attributes
    protected
    Definition Classes
    ParamsAndFeaturesWritable
  89. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  90. val outputAnnotatorType: AnnotatorType

    Output annotation type : WORD_EMBEDDINGS

    Output annotation type : WORD_EMBEDDINGS

    Definition Classes
    WordEmbeddings → HasOutputAnnotatorType
  91. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  92. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  93. val readCacheSize: IntParam

    Cache size for items retrieved from storage.

    Cache size for items retrieved from storage. Increase for performance but higher memory consumption

  94. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  95. def set[T](param: ProtectedParam[T], value: T): WordEmbeddings.this.type

    Sets the value for a protected Param.

    Sets the value for a protected Param.

    If the parameter was already set, it will not be set again. Default values do not count as a set value and can be overridden.

    T

    Type of the parameter

    param

    Protected parameter to set

    value

    Value for the parameter

    returns

    This object

    Definition Classes
    HasProtectedParams
  96. def set[T](feature: StructFeature[T], value: T): WordEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  97. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): WordEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  98. def set[T](feature: SetFeature[T], value: Set[T]): WordEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  99. def set[T](feature: ArrayFeature[T], value: Array[T]): WordEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  100. final def set(paramPair: ParamPair[_]): WordEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    Params
  101. final def set(param: String, value: Any): WordEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    Params
  102. final def set[T](param: Param[T], value: T): WordEmbeddings.this.type
    Definition Classes
    Params
  103. def setCaseSensitive(value: Boolean): WordEmbeddings.this.type

    Definition Classes
    HasCaseSensitiveProperties
  104. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): WordEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  105. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): WordEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  106. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): WordEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  107. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): WordEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  108. final def setDefault(paramPairs: ParamPair[_]*): WordEmbeddings.this.type
    Attributes
    protected
    Definition Classes
    Params
  109. final def setDefault[T](param: Param[T], value: T): WordEmbeddings.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  110. def setDimension(value: Int): WordEmbeddings.this.type

    Definition Classes
    HasEmbeddingsProperties
  111. def setEnableInMemoryStorage(value: Boolean): WordEmbeddings.this.type
    Definition Classes
    HasStorageOptions
  112. def setIncludeStorage(value: Boolean): WordEmbeddings.this.type
    Definition Classes
    HasStorageOptions
  113. final def setInputCols(value: String*): WordEmbeddings.this.type
    Definition Classes
    HasInputAnnotationCols
  114. def setInputCols(value: Array[String]): WordEmbeddings.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  115. def setLazyAnnotator(value: Boolean): WordEmbeddings.this.type
    Definition Classes
    CanBeLazy
  116. final def setOutputCol(value: String): WordEmbeddings.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  117. def setReadCacheSize(value: Int): WordEmbeddings.this.type

    Cache size for items retrieved from storage.

    Cache size for items retrieved from storage. Increase for performance but higher memory consumption.

  118. def setStoragePath(path: String, readAs: util.io.ReadAs.Value): WordEmbeddings.this.type

    Definition Classes
    HasStorage
  119. def setStoragePath(path: String, readAs: String): WordEmbeddings.this.type

    Definition Classes
    HasStorage
  120. def setStorageRef(value: String): WordEmbeddings.this.type
    Definition Classes
    HasStorageRef
  121. def setWriteBufferSize(value: Int): WordEmbeddings.this.type

    Buffer size limit before dumping to disk storage while writing.

  122. val storagePath: ExternalResourceParam

    Path to the external resource.

    Path to the external resource.

    Definition Classes
    HasStorage
  123. val storageRef: Param[String]

    Unique identifier for storage (Default: this.uid)

    Unique identifier for storage (Default: this.uid)

    Definition Classes
    HasStorageRef
  124. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  125. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  126. def train(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): WordEmbeddingsModel
    Definition Classes
    WordEmbeddings → AnnotatorApproach
  127. 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
  128. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  129. val uid: String
    Definition Classes
    WordEmbeddings → Identifiable
  130. 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
  131. def validateStorageRef(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): Unit
    Definition Classes
    HasStorageRef
  132. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  133. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  134. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  135. def wrapEmbeddingsMetadata(col: Column, embeddingsDim: Int, embeddingsRef: Option[String] = None): Column
    Attributes
    protected
    Definition Classes
    HasEmbeddingsProperties
  136. def wrapSentenceEmbeddingsMetadata(col: Column, embeddingsDim: Int, embeddingsRef: Option[String] = None): Column
    Attributes
    protected
    Definition Classes
    HasEmbeddingsProperties
  137. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
  138. val writeBufferSize: IntParam

    Buffer size limit before dumping to disk storage while writing

Inherited from HasEmbeddingsProperties

Inherited from HasProtectedParams

Inherited from HasStorage

Inherited from HasCaseSensitiveProperties

Inherited from HasStorageOptions

Inherited from HasStorageRef

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from AnnotatorApproach[WordEmbeddingsModel]

Inherited from CanBeLazy

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from HasOutputAnnotatorType

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from Estimator[WordEmbeddingsModel]

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