class GenericLogRegClassifierModel extends GenericClassifierModel with ParamsAndFeaturesWritable

Logistic regression classification

Please check out the Models Hub for available models.

Linear Supertypes
GenericClassifierModel, CheckLicense, HasSafeAnnotate[GenericClassifierModel], HandleExceptionParams, 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
Known Subclasses
FinanceFewShotClassifierModel, LegalFewShotClassifierModel, FewShotClassifierModel
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Inherited
  1. GenericLogRegClassifierModel
  2. GenericClassifierModel
  3. CheckLicense
  4. HasSafeAnnotate
  5. HandleExceptionParams
  6. HasSimpleAnnotate
  7. WriteTensorflowModel
  8. HasStorageRef
  9. AnnotatorModel
  10. CanBeLazy
  11. RawAnnotator
  12. HasOutputAnnotationCol
  13. HasInputAnnotationCols
  14. HasOutputAnnotatorType
  15. ParamsAndFeaturesWritable
  16. HasFeatures
  17. DefaultParamsWritable
  18. MLWritable
  19. Model
  20. Transformer
  21. PipelineStage
  22. Logging
  23. Params
  24. Serializable
  25. Serializable
  26. Identifiable
  27. AnyRef
  28. Any
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Visibility
  1. Public
  2. All

Instance Constructors

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

    uid

    a unique identifier for the instantiated AnnotatorModel

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
    GenericLogRegClassifierModel → 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. def checkValidEnvironment(spark: Option[SparkSession], scopes: Seq[String]): Unit
    Definition Classes
    CheckLicense
  16. def checkValidScope(scope: String): Unit
    Definition Classes
    CheckLicense
  17. def checkValidScopeAndEnvironment(scope: String, spark: Option[SparkSession], checkLp: Boolean): Unit
    Definition Classes
    CheckLicense
  18. def checkValidScopesAndEnvironment(scopes: Seq[String], spark: Option[SparkSession], checkLp: Boolean): Unit
    Definition Classes
    CheckLicense
  19. val classes: StringArrayParam
    Definition Classes
    GenericClassifierModel
  20. final def clear(param: Param[_]): GenericLogRegClassifierModel.this.type
    Definition Classes
    Params
  21. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  22. def copy(extra: ParamMap): GenericClassifierModel
    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  23. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  24. def createDatabaseConnection(database: Name): RocksDBConnection
    Definition Classes
    HasStorageRef
  25. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  26. def dfAnnotate: UserDefinedFunction
    Definition Classes
    HasSimpleAnnotate
  27. val doExceptionHandling: BooleanParam

    If true, exceptions are handled.

    If true, exceptions are handled. If exception causing data is passed to the model, a error annotation is emitted which has the exception message. Processing continues with the next one. This comes with a performance penalty.

    Definition Classes
    HandleExceptionParams
  28. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  29. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  30. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  31. def explainParams(): String
    Definition Classes
    Params
  32. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  33. def extraValidateMsg: String
    Attributes
    protected
    Definition Classes
    RawAnnotator
  34. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  35. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  36. val featureScaling: Param[String]

    Feature scaling method.

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

    Definition Classes
    GenericClassifierModel
  37. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  38. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  39. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  40. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  41. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  42. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  43. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  44. def getCategories(): Array[String]
    Definition Classes
    GenericClassifierModel
  45. def getCategoryName(id: Int): String
    Definition Classes
    GenericClassifierModel
  46. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  47. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  48. def getEncoder: GenericClassifierDataEncoder
    Definition Classes
    GenericClassifierModel
  49. def getFeatureScaling: String

    Get feature scaling method

    Get feature scaling method

    Definition Classes
    GenericClassifierModel
  50. def getInputCols: Array[String]
    Definition Classes
    HasInputAnnotationCols
  51. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  52. def getMultiClass: Boolean

    Gets the model multi class prediction mode

    Gets the model multi class prediction mode

    Definition Classes
    GenericClassifierModel
  53. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  54. final def getOutputCol: String
    Definition Classes
    HasOutputAnnotationCol
  55. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  56. def getStorageRef: String
    Definition Classes
    HasStorageRef
  57. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  58. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  59. def hasParent: Boolean
    Definition Classes
    Model
  60. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  61. val inExceptionMode: Boolean
    Attributes
    protected
    Definition Classes
    HasSafeAnnotate
  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 types : FEATURE_VECTOR

    Input annotator types : FEATURE_VECTOR

    Definition Classes
    GenericLogRegClassifierModel → GenericClassifierModel → HasInputAnnotationCols
  65. final val inputCols: StringArrayParam
    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. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  69. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  70. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  71. def loadModel(sparkSession: SparkSession, tfModel: TensorflowWrapper, categories: Array[String], encoder: GenericClassifierDataEncoder): GenericLogRegClassifierModel.this.type
  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. def model: TensorflowGenericClassifier
    Definition Classes
    GenericClassifierModel
  85. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  86. var multiClass: BooleanParam

    If multiClass is set, the model will return all the labels with corresponding scores.

    If multiClass is set, the model will return all the labels with corresponding scores. By default, multiClass is false.

    Definition Classes
    GenericClassifierModel
  87. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  88. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  89. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  90. def onWrite(path: String, spark: SparkSession): Unit
    Definition Classes
    GenericClassifierModel → ParamsAndFeaturesWritable
  91. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  92. val outputAnnotatorType: String

    Output annotator types : CATEGORY

    Output annotator types : CATEGORY

    Definition Classes
    GenericLogRegClassifierModel → GenericClassifierModel → HasOutputAnnotatorType
  93. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  94. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  95. var parent: Estimator[GenericClassifierModel]
    Definition Classes
    Model
  96. def safeAnnotate(annotations: Seq[Annotation]): Seq[Annotation]

    A protected method designed to safely annotate a sequence of Annotation objects by handling exceptions.

    A protected method designed to safely annotate a sequence of Annotation objects by handling exceptions.

    annotations

    A sequence of Annotation.

    returns

    A sequence of Annotation objects after processing, potentially containing error annotations.

    Attributes
    protected
    Definition Classes
    HasSafeAnnotate
  97. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  98. def scaleFeatures(features: Array[Array[Float]]): Array[Array[Float]]
    Attributes
    protected
    Definition Classes
    GenericClassifierModel
  99. def set[T](feature: StructFeature[T], value: T): GenericLogRegClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  100. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): GenericLogRegClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  101. def set[T](feature: SetFeature[T], value: Set[T]): GenericLogRegClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  102. def set[T](feature: ArrayFeature[T], value: Array[T]): GenericLogRegClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  103. final def set(paramPair: ParamPair[_]): GenericLogRegClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  104. final def set(param: String, value: Any): GenericLogRegClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  105. final def set[T](param: Param[T], value: T): GenericLogRegClassifierModel.this.type
    Definition Classes
    Params
  106. def setCategoryNames(categoryNames: Array[String]): GenericLogRegClassifierModel.this.type
    Definition Classes
    GenericClassifierModel
  107. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): GenericLogRegClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  108. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): GenericLogRegClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  109. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): GenericLogRegClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  110. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): GenericLogRegClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  111. final def setDefault(paramPairs: ParamPair[_]*): GenericLogRegClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  112. final def setDefault[T](param: Param[T], value: T): GenericLogRegClassifierModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  113. def setDoExceptionHandling(value: Boolean): GenericLogRegClassifierModel.this.type

    If true, exceptions are handled.

    If true, exceptions are handled. If exception causing data is passed to the model, a error annotation is emitted which has the exception message. Processing continues with the next one. This comes with a performance penalty.

    Definition Classes
    HandleExceptionParams
  114. def setEncoder(encoder: GenericClassifierDataEncoder): GenericLogRegClassifierModel.this.type
    Definition Classes
    GenericClassifierModel
  115. def setFeatureScaling(featureScaling: String): GenericLogRegClassifierModel.this.type

    Set the feature scaling method.

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

    Definition Classes
    GenericClassifierModel
  116. final def setInputCols(value: String*): GenericLogRegClassifierModel.this.type
    Definition Classes
    HasInputAnnotationCols
  117. def setInputCols(value: Array[String]): GenericLogRegClassifierModel.this.type
    Definition Classes
    HasInputAnnotationCols
  118. def setLazyAnnotator(value: Boolean): GenericLogRegClassifierModel.this.type
    Definition Classes
    CanBeLazy
  119. def setMultiClass(value: Boolean): GenericLogRegClassifierModel.this.type

    Sets the model in multi class prediction mode

    Sets the model in multi class prediction mode

    Definition Classes
    GenericClassifierModel
  120. final def setOutputCol(value: String): GenericLogRegClassifierModel.this.type
    Definition Classes
    HasOutputAnnotationCol
  121. def setParent(parent: Estimator[GenericClassifierModel]): GenericClassifierModel
    Definition Classes
    Model
  122. def setStorageRef(value: String): GenericLogRegClassifierModel.this.type
    Definition Classes
    HasStorageRef
  123. def setTensorflowModel(spark: SparkSession, tf: TensorflowWrapper): GenericLogRegClassifierModel.this.type
    Definition Classes
    GenericClassifierModel
  124. val storageRef: Param[String]
    Definition Classes
    HasStorageRef
  125. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  126. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  127. final def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    AnnotatorModel → Transformer
  128. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  129. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  130. final def transformSchema(schema: StructType): StructType
    Definition Classes
    RawAnnotator → PipelineStage
  131. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  132. val uid: String
    Definition Classes
    GenericLogRegClassifierModel → GenericClassifierModel → Identifiable
  133. def validate(schema: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  134. def validateStorageRef(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): Unit
    Definition Classes
    HasStorageRef
  135. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  136. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  137. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  138. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  139. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
  140. def writeTensorflowHub(path: String, tfPath: String, spark: SparkSession, suffix: String): Unit
    Definition Classes
    WriteTensorflowModel
  141. def writeTensorflowModel(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]]): Unit
    Definition Classes
    WriteTensorflowModel
  142. def writeTensorflowModelV2(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]], savedSignatures: Option[Map[String, String]]): Unit
    Definition Classes
    WriteTensorflowModel

Inherited from GenericClassifierModel

Inherited from CheckLicense

Inherited from HasSafeAnnotate[GenericClassifierModel]

Inherited from HandleExceptionParams

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

Parameters

Annotator types

Required input and expected output annotator types

Members

Parameter setters

Parameter getters