Packages

class GenericClassifierModel extends AnnotatorModel[GenericClassifierModel] with HasStorageRef with ParamsAndFeaturesWritable with WriteTensorflowModel with HasSimpleAnnotate[GenericClassifierModel] with Licensed

The Generic Classifier is generic single-label classifier which uses pre-generated Tensorflow graphs. The model operates on FEATURE_VECTOR annotations which can be produced using FeatureAssembler.

Linear Supertypes
Licensed, HasSimpleAnnotate[GenericClassifierModel], WriteTensorflowModel, HasStorageRef, AnnotatorModel[GenericClassifierModel], CanBeLazy, RawAnnotator[GenericClassifierModel], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[GenericClassifierModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. GenericClassifierModel
  2. Licensed
  3. HasSimpleAnnotate
  4. WriteTensorflowModel
  5. HasStorageRef
  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 GenericClassifierModel()
  2. new GenericClassifierModel(uid: String)

Type Members

  1. type AnnotationContent = Seq[Row]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  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 _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
    GenericClassifierModel → HasSimpleAnnotate
  12. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  13. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Attributes
    protected
    Definition Classes
    GenericClassifierModel → AnnotatorModel
  14. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  15. final def clear(param: Param[_]): GenericClassifierModel.this.type
    Definition Classes
    Params
  16. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  17. def copy(extra: ParamMap): GenericClassifierModel
    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  18. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  19. def createDatabaseConnection(database: Name): RocksDBConnection
    Definition Classes
    HasStorageRef
  20. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  21. def dfAnnotate: UserDefinedFunction
    Definition Classes
    HasSimpleAnnotate
  22. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  23. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  24. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  25. def explainParams(): String
    Definition Classes
    Params
  26. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  27. def extraValidateMsg: String
    Attributes
    protected
    Definition Classes
    RawAnnotator
  28. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  29. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  30. val featureScaling: Param[String]

    Feature scaling method.

    Feature scaling method. Possible values are 'zscore', 'minmax' or empty (no scaling)

  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. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  34. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  35. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  36. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  37. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  38. def getCategories(): Array[String]

    Get all categories

  39. def getCategoryName(id: Int): String

  40. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  41. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  42. def getEncoder: GenericClassifierDataEncoder
  43. def getFeatureScaling: String

    Get feature scaling method

  44. def getInputCols: Array[String]
    Definition Classes
    HasInputAnnotationCols
  45. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  46. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  47. final def getOutputCol: String
    Definition Classes
    HasOutputAnnotationCol
  48. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  49. def getStorageRef: String
    Definition Classes
    HasStorageRef
  50. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  51. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  52. def hasParent: Boolean
    Definition Classes
    Model
  53. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  54. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  55. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  56. val inputAnnotatorTypes: Array[AnnotatorType]

    Output annotator type : SENTENCE_EMBEDDINGS

    Output annotator type : SENTENCE_EMBEDDINGS

    Definition Classes
    GenericClassifierModel → HasInputAnnotationCols
  57. final val inputCols: StringArrayParam
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  58. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  59. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  60. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  61. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  62. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  63. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  64. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  66. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  69. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  71. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  75. def model: TensorflowGenericClassifier
  76. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  77. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  78. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  79. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  80. def onWrite(path: String, spark: SparkSession): Unit
    Definition Classes
    GenericClassifierModel → ParamsAndFeaturesWritable
  81. val outputAnnotatorType: String

    Output annotator type : CATEGORY

    Output annotator type : CATEGORY

    Definition Classes
    GenericClassifierModel → HasOutputAnnotatorType
  82. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  83. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  84. var parent: Estimator[GenericClassifierModel]
    Definition Classes
    Model
  85. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  86. def scaleFeatures(features: Array[Array[Float]]): Array[Array[Float]]
    Attributes
    protected
  87. def set[T](feature: StructFeature[T], value: T): GenericClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  88. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): GenericClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  89. def set[T](feature: SetFeature[T], value: Set[T]): GenericClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  90. def set[T](feature: ArrayFeature[T], value: Array[T]): GenericClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  91. final def set(paramPair: ParamPair[_]): GenericClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  92. final def set(param: String, value: Any): GenericClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  93. final def set[T](param: Param[T], value: T): GenericClassifierModel.this.type
    Definition Classes
    Params
  94. def setCategoryNames(categoryNames: Array[String]): GenericClassifierModel.this.type

  95. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): GenericClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  96. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): GenericClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  97. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): GenericClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  98. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): GenericClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  99. final def setDefault(paramPairs: ParamPair[_]*): GenericClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  100. final def setDefault[T](param: Param[T], value: T): GenericClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  101. def setEncoder(encoder: GenericClassifierDataEncoder): GenericClassifierModel.this.type
  102. def setFeatureScaling(featureScaling: String): GenericClassifierModel.this.type

    Set the feature scaling method.

    Set the feature scaling method. Possible values are 'zscore', 'minmax' or empty (no scaling)

  103. final def setInputCols(value: String*): GenericClassifierModel.this.type
    Definition Classes
    HasInputAnnotationCols
  104. final def setInputCols(value: Array[String]): GenericClassifierModel.this.type
    Definition Classes
    HasInputAnnotationCols
  105. def setLazyAnnotator(value: Boolean): GenericClassifierModel.this.type
    Definition Classes
    CanBeLazy
  106. final def setOutputCol(value: String): GenericClassifierModel.this.type
    Definition Classes
    HasOutputAnnotationCol
  107. def setParent(parent: Estimator[GenericClassifierModel]): GenericClassifierModel
    Definition Classes
    Model
  108. def setStorageRef(value: String): GenericClassifierModel.this.type
    Definition Classes
    HasStorageRef
  109. def setTensorflowModel(spark: SparkSession, tf: TensorflowWrapper): GenericClassifierModel.this.type
  110. val storageRef: Param[String]
    Definition Classes
    HasStorageRef
  111. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  112. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  113. final def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    AnnotatorModel → Transformer
  114. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  115. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  116. final def transformSchema(schema: StructType): StructType
    Definition Classes
    RawAnnotator → PipelineStage
  117. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  118. val uid: String
    Definition Classes
    GenericClassifierModel → Identifiable
  119. def validate(schema: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  120. def validateStorageRef(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): Unit
    Definition Classes
    HasStorageRef
  121. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  122. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  123. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  124. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  125. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
  126. def writeTensorflowHub(path: String, tfPath: String, spark: SparkSession, suffix: String): Unit
    Definition Classes
    WriteTensorflowModel
  127. def writeTensorflowModel(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]]): Unit
    Definition Classes
    WriteTensorflowModel
  128. def writeTensorflowModelV2(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]]): Unit
    Definition Classes
    WriteTensorflowModel

Inherited from Licensed

Inherited from HasSimpleAnnotate[GenericClassifierModel]

Inherited from WriteTensorflowModel

Inherited from HasStorageRef

Inherited from AnnotatorModel[GenericClassifierModel]

Inherited from CanBeLazy

Inherited from RawAnnotator[GenericClassifierModel]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[GenericClassifierModel]

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

anno

getParam

param

setParam

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