Class/Object

com.johnsnowlabs.nlp.annotators.sda.pragmatic

SentimentDetectorModel

Related Docs: object SentimentDetectorModel | package pragmatic

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class SentimentDetectorModel extends AnnotatorModel[SentimentDetectorModel]

Gives a good or bad score to a sentence based on the approach used

Linear Supertypes
AnnotatorModel[SentimentDetectorModel], HasOutputAnnotationCol, HasInputAnnotationCols, HasAnnotatorType, DefaultParamsWritable, MLWritable, Model[SentimentDetectorModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. SentimentDetectorModel
  2. AnnotatorModel
  3. HasOutputAnnotationCol
  4. HasInputAnnotationCols
  5. HasAnnotatorType
  6. DefaultParamsWritable
  7. MLWritable
  8. Model
  9. Transformer
  10. PipelineStage
  11. Logging
  12. Params
  13. Serializable
  14. Serializable
  15. Identifiable
  16. AnyRef
  17. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new SentimentDetectorModel()

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  2. new SentimentDetectorModel(uid: String)

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    uid

    internal uid needed for saving annotator to disk

Type Members

  1. type AnnotatorType = String

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    Definition Classes
    HasAnnotatorType

Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T

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    Attributes
    protected
    Definition Classes
    Params
  4. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  5. def annotate(annotations: Seq[Annotation]): Seq[Annotation]

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    Tokens are needed to identify each word in a sentence boundary POS tags are optionally submitted to the model in case they are needed Lemmas are another optional annotator for some models Bounds of sentiment are hardcoded to 0 as they render useless

    Tokens are needed to identify each word in a sentence boundary POS tags are optionally submitted to the model in case they are needed Lemmas are another optional annotator for some models Bounds of sentiment are hardcoded to 0 as they render useless

    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
    SentimentDetectorModelAnnotatorModel
  6. val annotatorType: AnnotatorType

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  7. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  8. final def clear(param: Param[_]): SentimentDetectorModel.this.type

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    Definition Classes
    Params
  9. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  10. def copy(extra: ParamMap): SentimentDetectorModel

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    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    AnnotatorModel → Model → Transformer → PipelineStage → Params
  11. def copyValues[T <: Params](to: T, extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params
  12. final def defaultCopy[T <: Params](extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params
  13. val dictFormat: Param[String]

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  14. val dictPath: Param[String]

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  15. val dictSeparator: Param[String]

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  16. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  17. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  18. def explainParam(param: Param[_]): String

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    Definition Classes
    Params
  19. def explainParams(): String

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    Definition Classes
    Params
  20. final def extractParamMap(): ParamMap

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    Definition Classes
    Params
  21. final def extractParamMap(extra: ParamMap): ParamMap

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    Definition Classes
    Params
  22. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  23. final def get[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  24. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any
  25. final def getDefault[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  26. def getDictFormat: String

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  27. def getDictPath: String

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  28. def getDictSeparator: String

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  29. final def getInputCols: Array[String]

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    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  30. final def getOrDefault[T](param: Param[T]): T

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    Definition Classes
    Params
  31. final def getOutputCol: String

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    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  32. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  33. final def hasDefault[T](param: Param[T]): Boolean

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    Definition Classes
    Params
  34. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params
  35. def hasParent: Boolean

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    Definition Classes
    Model
  36. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  37. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  38. final val inputCols: StringArrayParam

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    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
  39. final def isDefined(param: Param[_]): Boolean

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    Definition Classes
    Params
  40. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  41. final def isSet(param: Param[_]): Boolean

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    Definition Classes
    Params
  42. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  43. def log: Logger

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    Attributes
    protected
    Definition Classes
    Logging
  44. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  45. def logDebug(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  46. def logError(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  47. def logError(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  48. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  49. def logInfo(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  50. def logName: String

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    Attributes
    protected
    Definition Classes
    Logging
  51. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  52. def logTrace(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  53. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  54. def logWarning(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  55. lazy val model: PragmaticScorer

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  56. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  57. final def notify(): Unit

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    Definition Classes
    AnyRef
  58. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  59. final val outputCol: Param[String]

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    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  60. lazy val params: Array[Param[_]]

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    Definition Classes
    Params
  61. var parent: Estimator[SentimentDetectorModel]

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    Definition Classes
    Model
  62. val requiredAnnotatorTypes: Array[AnnotatorType]

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    Annotator reference id.

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

    Definition Classes
    SentimentDetectorModelHasInputAnnotationCols
  63. def save(path: String): Unit

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    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  64. final def set(paramPair: ParamPair[_]): SentimentDetectorModel.this.type

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    Attributes
    protected
    Definition Classes
    Params
  65. final def set(param: String, value: Any): SentimentDetectorModel.this.type

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    Attributes
    protected
    Definition Classes
    Params
  66. final def set[T](param: Param[T], value: T): SentimentDetectorModel.this.type

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    Definition Classes
    Params
  67. final def setDefault(paramPairs: ParamPair[_]*): SentimentDetectorModel.this.type

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    Attributes
    protected
    Definition Classes
    Params
  68. final def setDefault[T](param: Param[T], value: T): SentimentDetectorModel.this.type

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    Attributes
    protected
    Definition Classes
    Params
  69. def setDictFormat(format: String): SentimentDetectorModel.this.type

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  70. def setDictPath(path: String): SentimentDetectorModel.this.type

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  71. def setDictSeparator(separator: String): SentimentDetectorModel.this.type

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  72. final def setInputCols(value: String*): SentimentDetectorModel.this.type

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    Definition Classes
    HasInputAnnotationCols
  73. final def setInputCols(value: Array[String]): SentimentDetectorModel.this.type

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    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  74. final def setOutputCol(value: String): SentimentDetectorModel.this.type

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    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  75. def setParent(parent: Estimator[SentimentDetectorModel]): SentimentDetectorModel

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    Definition Classes
    Model
  76. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  77. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any
  78. final def transform(dataset: Dataset[_]): DataFrame

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    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
  79. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  80. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  81. final def transformSchema(schema: StructType): StructType

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    requirement for pipeline transformation validation.

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

    Definition Classes
    AnnotatorModel → PipelineStage
  82. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  83. val uid: String

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    internal uid needed for saving annotator to disk

    internal uid needed for saving annotator to disk

    Definition Classes
    SentimentDetectorModel → Identifiable
  84. def validate(schema: StructType): Boolean

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    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
    HasInputAnnotationCols
  85. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  86. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  87. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  88. def write: MLWriter

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    Definition Classes
    DefaultParamsWritable → MLWritable

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasAnnotatorType

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[SentimentDetectorModel]

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

Ungrouped