class PosologyREModel extends GenericREModel
Instantiated RelationExtractionModel for extracting relationships between different recognized drug entitites.
This class is not intended to be directly used, please use the RelationExtractionModel instead.
Possible values are
"DRUG-DOSAGE", "DRUG-ADE", "DRUG-FORM", "DRUG-FREQUENCY", "DRUG-ROUTE", "DRUG-REASON", "DRUG-STRENGTH", "DRUG-DURATION"
.
Please see the
Models Hub for available models.
- See also
RelationExtractionModel to use the model
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- PosologyREModel
- GenericREModel
- RelationExtractionModel
- HasSafeAnnotate
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- WriteTensorflowModel
- HasStorageRef
- AnnotatorModel
- CanBeLazy
- RawAnnotator
- HasOutputAnnotationCol
- HasInputAnnotationCols
- HasOutputAnnotatorType
- ParamsAndFeaturesWritable
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- Definition Classes
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final
def
##(): Int
- Definition Classes
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final
def
$[T](param: Param[T]): T
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def
$$[T](feature: StructFeature[T]): T
- Attributes
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def
$$[K, V](feature: MapFeature[K, V]): Map[K, V]
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def
$$[T](feature: SetFeature[T]): Set[T]
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def
$$[T](feature: ArrayFeature[T]): Array[T]
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final
def
==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
def
_transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
- Attributes
- protected
- Definition Classes
- AnnotatorModel
-
def
afterAnnotate(dataset: DataFrame): DataFrame
- Attributes
- protected
- Definition Classes
- AnnotatorModel
-
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
- RelationExtractionModel → GenericClassifierModel → HasSimpleAnnotate
-
final
def
asInstanceOf[T0]: T0
- Definition Classes
- Any
-
def
beforeAnnotate(dataset: Dataset[_]): Dataset[_]
- Attributes
- protected
- Definition Classes
- GenericClassifierModel → AnnotatorModel
-
def
categorizeRel(relation: RelationInstance): (Long, Float, Array[Float])
- Definition Classes
- GenericREModel → RelationExtractionModel
-
final
def
checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
- Attributes
- protected
- Definition Classes
- HasInputAnnotationCols
-
def
checkValidEnvironment(spark: Option[SparkSession], scopes: Seq[String]): Unit
- Definition Classes
- CheckLicense
-
def
checkValidScope(scope: String): Unit
- Definition Classes
- CheckLicense
-
def
checkValidScopeAndEnvironment(scope: String, spark: Option[SparkSession], checkLp: Boolean): Unit
- Definition Classes
- CheckLicense
-
def
checkValidScopesAndEnvironment(scopes: Seq[String], spark: Option[SparkSession], checkLp: Boolean): Unit
- Definition Classes
- CheckLicense
-
val
classes: StringArrayParam
- Definition Classes
- GenericClassifierModel
-
final
def
clear(param: Param[_]): PosologyREModel.this.type
- Definition Classes
- Params
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def
clone(): AnyRef
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- protected[lang]
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- @throws( ... ) @native()
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def
copy(extra: ParamMap): GenericClassifierModel
- Definition Classes
- RawAnnotator → Model → Transformer → PipelineStage → Params
-
def
copyValues[T <: Params](to: T, extra: ParamMap): T
- Attributes
- protected
- Definition Classes
- Params
-
def
createDatabaseConnection(database: Name): RocksDBConnection
- Definition Classes
- HasStorageRef
-
var
customLabels: MapFeature[String, String]
Custom relation labels
Custom relation labels
- Definition Classes
- RelationExtractionModel
-
final
def
defaultCopy[T <: Params](extra: ParamMap): T
- Attributes
- protected
- Definition Classes
- Params
-
def
dfAnnotate: UserDefinedFunction
- Definition Classes
- HasSimpleAnnotate
-
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
-
final
def
eq(arg0: AnyRef): Boolean
- Definition Classes
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def
equals(arg0: Any): Boolean
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def
explainParam(param: Param[_]): String
- Definition Classes
- Params
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def
explainParams(): String
- Definition Classes
- Params
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def
extraValidate(structType: StructType): Boolean
- Attributes
- protected
- Definition Classes
- RawAnnotator
-
def
extraValidateMsg: String
- Attributes
- protected
- Definition Classes
- RawAnnotator
-
final
def
extractParamMap(): ParamMap
- Definition Classes
- Params
-
final
def
extractParamMap(extra: ParamMap): ParamMap
- Definition Classes
- Params
-
val
featureScaling: Param[String]
Feature scaling method.
Feature scaling method. Possible values are 'zscore', 'minmax' or empty (no scaling)
- Definition Classes
- GenericClassifierModel
-
val
features: ArrayBuffer[Feature[_, _, _]]
- Definition Classes
- HasFeatures
-
def
finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( classOf[java.lang.Throwable] )
-
def
get[T](feature: StructFeature[T]): Option[T]
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
get[T](feature: SetFeature[T]): Option[Set[T]]
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
get[T](feature: ArrayFeature[T]): Option[Array[T]]
- Attributes
- protected
- Definition Classes
- HasFeatures
-
final
def
get[T](param: Param[T]): Option[T]
- Definition Classes
- Params
-
def
getCategories(): Array[String]
- Definition Classes
- GenericClassifierModel
-
def
getCategoryName(id: Int): String
- Definition Classes
- GenericREModel → GenericClassifierModel
-
final
def
getClass(): Class[_]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
-
def
getClasses: Array[String]
Proxy to getCategories
Proxy to getCategories
- Definition Classes
- RelationExtractionModel
-
def
getCustomLabel(label: String): String
- Definition Classes
- RelationExtractionModel
-
def
getCustomLabels: Map[String, String]
Custom relation labels
Custom relation labels
- Definition Classes
- RelationExtractionModel
-
final
def
getDefault[T](param: Param[T]): Option[T]
- Definition Classes
- Params
-
def
getEncoder: GenericClassifierDataEncoder
- Definition Classes
- GenericClassifierModel
-
def
getFeatureScaling: String
Get feature scaling method
Get feature scaling method
- Definition Classes
- GenericClassifierModel
-
def
getInputCols: Array[String]
- Definition Classes
- HasInputAnnotationCols
-
def
getLazyAnnotator: Boolean
- Definition Classes
- CanBeLazy
-
def
getMaxSyntacticDistance: Int
Maximal syntactic distance, as threshold (Default: 0)
Maximal syntactic distance, as threshold (Default: 0)
- Definition Classes
- RelationExtractionModel
-
def
getMultiClass: Boolean
Gets the model multi class prediction mode
Gets the model multi class prediction mode
- Definition Classes
- GenericClassifierModel
-
final
def
getOrDefault[T](param: Param[T]): T
- Definition Classes
- Params
-
final
def
getOutputCol: String
- Definition Classes
- HasOutputAnnotationCol
-
def
getParam(paramName: String): Param[Any]
- Definition Classes
- Params
-
def
getPredictionThreshold: Float
Minimal activation of the target unit to encode a new relation instance (Default: 0.5f)
Minimal activation of the target unit to encode a new relation instance (Default: 0.5f)
- Definition Classes
- RelationExtractionModel
-
def
getRelationPairs: Array[String]
List of dash-separated pairs of named entities ("ENTITY1-ENTITY2", e.g.
List of dash-separated pairs of named entities ("ENTITY1-ENTITY2", e.g. "Biomarker-RelativeDay"), which will be processed
- Definition Classes
- RelationExtractionModel
-
def
getRelationPairsCaseSensitive: Boolean
Gets the case sensitivity of relation pairs
Gets the case sensitivity of relation pairs
- Definition Classes
- RelationExtractionModel
-
def
getRelationTypePerPair: Map[String, Array[String]]
Get the lists of entity pairs allowed for a given relation
Get the lists of entity pairs allowed for a given relation
- Definition Classes
- RelationExtractionModel
-
def
getRelationTypePerPairStr: String
Get a string representation of the lists of entity pairs allowed for a given relation
Get a string representation of the lists of entity pairs allowed for a given relation
- Definition Classes
- RelationExtractionModel
-
def
getStorageRef: String
- Definition Classes
- HasStorageRef
-
final
def
hasDefault[T](param: Param[T]): Boolean
- Definition Classes
- Params
-
def
hasParam(paramName: String): Boolean
- Definition Classes
- Params
-
def
hasParent: Boolean
- Definition Classes
- Model
-
def
hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
-
val
inExceptionMode: Boolean
- Attributes
- protected
- Definition Classes
- HasSafeAnnotate
-
def
initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
- Attributes
- protected
- Definition Classes
- Logging
-
def
initializeLogIfNecessary(isInterpreter: Boolean): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
val
inputAnnotatorTypes: Array[AnnotatorType]
Input annotator types : WORD_EMBEDDINGS, POS, CHUNK, DEPENDENCY
Input annotator types : WORD_EMBEDDINGS, POS, CHUNK, DEPENDENCY
- Definition Classes
- RelationExtractionModel → GenericClassifierModel → HasInputAnnotationCols
-
final
val
inputCols: StringArrayParam
- Attributes
- protected
- Definition Classes
- HasInputAnnotationCols
-
final
def
isDefined(param: Param[_]): Boolean
- Definition Classes
- Params
-
final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
-
final
def
isSet(param: Param[_]): Boolean
- Definition Classes
- Params
-
def
isTraceEnabled(): Boolean
- Attributes
- protected
- Definition Classes
- Logging
-
val
lazyAnnotator: BooleanParam
- Definition Classes
- CanBeLazy
-
def
loadModel(sparkSession: SparkSession, tfModel: TensorflowWrapper, categories: Array[String], encoder: GenericClassifierDataEncoder, nerTags: Array[String]): PosologyREModel.this.type
- Definition Classes
- RelationExtractionModel
-
def
log: Logger
- Attributes
- protected
- Definition Classes
- Logging
-
def
logDebug(msg: ⇒ String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logDebug(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logError(msg: ⇒ String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logError(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logInfo(msg: ⇒ String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logInfo(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logName: String
- Attributes
- protected
- Definition Classes
- Logging
-
def
logTrace(msg: ⇒ String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logTrace(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logWarning(msg: ⇒ String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logWarning(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
var
maxSyntacticDistance: IntParam
Maximal syntactic distance, as threshold (Default: 0)
Maximal syntactic distance, as threshold (Default: 0)
- Definition Classes
- RelationExtractionModel
-
def
model: TensorflowGenericClassifier
- Definition Classes
- GenericREModel → GenericClassifierModel
-
def
msgHelper(schema: StructType): String
- Attributes
- protected
- Definition Classes
- HasInputAnnotationCols
-
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
-
final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
final
def
notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
final
def
notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
def
onWrite(path: String, spark: SparkSession): Unit
- Definition Classes
- GenericClassifierModel → ParamsAndFeaturesWritable
-
val
optionalInputAnnotatorTypes: Array[String]
- Definition Classes
- HasInputAnnotationCols
-
val
outputAnnotatorType: String
Output annotator types : CATEGORY
Output annotator types : CATEGORY
- Definition Classes
- RelationExtractionModel → GenericClassifierModel → HasOutputAnnotatorType
-
final
val
outputCol: Param[String]
- Attributes
- protected
- Definition Classes
- HasOutputAnnotationCol
-
lazy val
params: Array[Param[_]]
- Definition Classes
- Params
-
var
parent: Estimator[GenericClassifierModel]
- Definition Classes
- Model
-
var
predictionThreshold: FloatParam
Minimal activation of the target unit to encode a new relation instance (Default: 0.5f)
Minimal activation of the target unit to encode a new relation instance (Default: 0.5f)
- Definition Classes
- RelationExtractionModel
-
var
relationPairs: Param[String]
List of dash-separated pairs of named entities ("ENTITY1-ENTITY2", e.g.
List of dash-separated pairs of named entities ("ENTITY1-ENTITY2", e.g. "Biomarker-RelativeDay"), which will be processed
- Definition Classes
- RelationExtractionModel
-
var
relationPairsCaseSensitive: BooleanParam
Determines whether relation pairs are case sensitive
Determines whether relation pairs are case sensitive
- Definition Classes
- RelationExtractionModel
-
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
-
def
save(path: String): Unit
- Definition Classes
- MLWritable
- Annotations
- @Since( "1.6.0" ) @throws( ... )
-
def
scaleFeatures(features: Array[Array[Float]]): Array[Array[Float]]
- Attributes
- protected
- Definition Classes
- GenericClassifierModel
-
def
set[T](feature: StructFeature[T], value: T): PosologyREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
set[K, V](feature: MapFeature[K, V], value: Map[K, V]): PosologyREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
set[T](feature: SetFeature[T], value: Set[T]): PosologyREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
set[T](feature: ArrayFeature[T], value: Array[T]): PosologyREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
final
def
set(paramPair: ParamPair[_]): PosologyREModel.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
set(param: String, value: Any): PosologyREModel.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
set[T](param: Param[T], value: T): PosologyREModel.this.type
- Definition Classes
- Params
-
def
setCategoryNames(categoryNames: Array[String]): PosologyREModel.this.type
- Definition Classes
- GenericClassifierModel
-
def
setCustomLabels(labels: HashMap[String, String]): PosologyREModel.this.type
- Definition Classes
- RelationExtractionModel
-
def
setCustomLabels(labels: Map[String, String]): PosologyREModel.this.type
Set custom relation labels
Set custom relation labels
- Definition Classes
- RelationExtractionModel
-
def
setDefault[T](feature: StructFeature[T], value: () ⇒ T): PosologyREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): PosologyREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): PosologyREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): PosologyREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
final
def
setDefault(paramPairs: ParamPair[_]*): PosologyREModel.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
setDefault[T](param: Param[T], value: T): PosologyREModel.this.type
- Attributes
- protected
- Definition Classes
- Params
-
def
setDoExceptionHandling(value: Boolean): PosologyREModel.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
-
def
setEncoder(encoder: GenericClassifierDataEncoder): PosologyREModel.this.type
- Definition Classes
- GenericClassifierModel
-
def
setFeatureScaling(featureScaling: String): PosologyREModel.this.type
Set the feature scaling method.
Set the feature scaling method. Possible values are 'zscore', 'minmax' or empty (no scaling)
- Definition Classes
- GenericClassifierModel
-
final
def
setInputCols(value: String*): PosologyREModel.this.type
- Definition Classes
- HasInputAnnotationCols
-
def
setInputCols(value: Array[String]): PosologyREModel.this.type
- Definition Classes
- HasInputAnnotationCols
-
def
setLazyAnnotator(value: Boolean): PosologyREModel.this.type
- Definition Classes
- CanBeLazy
-
def
setMaxSyntacticDistance(maxSyntacticDistance: Int): PosologyREModel.this.type
Maximal syntactic distance, as threshold (Default: 0)
Maximal syntactic distance, as threshold (Default: 0)
- Definition Classes
- RelationExtractionModel
-
def
setMultiClass(value: Boolean): PosologyREModel.this.type
Sets the model in multi class prediction mode
Sets the model in multi class prediction mode
- Definition Classes
- GenericClassifierModel
-
final
def
setOutputCol(value: String): PosologyREModel.this.type
- Definition Classes
- HasOutputAnnotationCol
-
def
setParent(parent: Estimator[GenericClassifierModel]): GenericClassifierModel
- Definition Classes
- Model
-
def
setPredictionThreshold(predictionThreshold: Float): PosologyREModel.this.type
Minimal activation of the target unit to encode a new relation instance (Default: 0.5f)
Minimal activation of the target unit to encode a new relation instance (Default: 0.5f)
- Definition Classes
- RelationExtractionModel
-
def
setRelationPairs(relationPairs: Array[String]): PosologyREModel.this.type
List of dash-separated pairs of named entities ("ENTITY1-ENTITY2", e.g.
List of dash-separated pairs of named entities ("ENTITY1-ENTITY2", e.g. "Biomarker-RelativeDay"), which will be processed
- Definition Classes
- RelationExtractionModel
-
def
setRelationPairsCaseSensitive(value: Boolean): PosologyREModel.this.type
Sets the case sensitivity of relation pairs
Sets the case sensitivity of relation pairs
- Definition Classes
- RelationExtractionModel
-
def
setRelationTypePerPair(categories: HashMap[String, List[String]]): PosologyREModel.this.type
Set the lists of entity pairs allowed for a given relation
Set the lists of entity pairs allowed for a given relation
- Definition Classes
- RelationExtractionModel
-
def
setRelationTypePerPair(categories: Map[String, Array[String]]): PosologyREModel.this.type
Set the lists of entity pairs allowed for a given relation
Set the lists of entity pairs allowed for a given relation
- Definition Classes
- RelationExtractionModel
-
def
setStorageRef(value: String): PosologyREModel.this.type
- Definition Classes
- HasStorageRef
-
def
setTensorflowModel(spark: SparkSession, tf: TensorflowWrapper): PosologyREModel.this.type
- Definition Classes
- GenericClassifierModel
-
val
storageRef: Param[String]
- Definition Classes
- HasStorageRef
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
-
def
toString(): String
- Definition Classes
- Identifiable → AnyRef → Any
-
final
def
transform(dataset: Dataset[_]): DataFrame
- Definition Classes
- AnnotatorModel → Transformer
-
def
transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
- Definition Classes
- Transformer
- Annotations
- @Since( "2.0.0" )
-
def
transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
- Definition Classes
- Transformer
- Annotations
- @Since( "2.0.0" ) @varargs()
-
final
def
transformSchema(schema: StructType): StructType
- Definition Classes
- RawAnnotator → PipelineStage
-
def
transformSchema(schema: StructType, logging: Boolean): StructType
- Attributes
- protected
- Definition Classes
- PipelineStage
- Annotations
- @DeveloperApi()
-
val
uid: String
- Definition Classes
- PosologyREModel → GenericREModel → RelationExtractionModel → GenericClassifierModel → Identifiable
-
def
validate(schema: StructType): Boolean
- Attributes
- protected
- Definition Classes
- RawAnnotator
-
def
validateStorageRef(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): Unit
- Definition Classes
- HasStorageRef
-
final
def
wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()
-
def
wrapColumnMetadata(col: Column): Column
- Attributes
- protected
- Definition Classes
- RawAnnotator
-
def
write: MLWriter
- Definition Classes
- ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
-
def
writeTensorflowHub(path: String, tfPath: String, spark: SparkSession, suffix: String): Unit
- Definition Classes
- WriteTensorflowModel
-
def
writeTensorflowModel(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]]): Unit
- Definition Classes
- GenericREModel → WriteTensorflowModel
-
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 GenericREModel
Inherited from RelationExtractionModel
Inherited from HasSafeAnnotate[GenericClassifierModel]
Inherited from HandleExceptionParams
Inherited from GenericClassifierModel
Inherited from CheckLicense
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