class GenericREModel extends RelationExtractionModel with HasStorageRef with ParamsAndFeaturesWritable with CheckLicense
Instantiated RelationExtractionModel for extracting relationships between any entitites. This class is not intended to be directly used, please use the RelationExtractionModel instead. Pairs of entitie should be specified using setRelationPairs Please see the Models Hub for available models.
- See also
RelationExtractionModel to use the model
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- GenericREModel
- RelationExtractionModel
- GenericClassifierModel
- CheckLicense
- HasSafeAnnotate
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- WriteTensorflowModel
- HasStorageRef
- GenericClassifierParams
- AnnotatorModel
- CanBeLazy
- RawAnnotator
- HasOutputAnnotationCol
- HasInputAnnotationCols
- HasOutputAnnotatorType
- ParamsAndFeaturesWritable
- HasFeatures
- DefaultParamsWritable
- MLWritable
- Model
- Transformer
- PipelineStage
- Logging
- Params
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final
def
!=(arg0: Any): Boolean
- Definition Classes
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final
def
##(): Int
- Definition Classes
- AnyRef → Any
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final
def
$[T](param: Param[T]): T
- Attributes
- protected
- Definition Classes
- Params
-
def
$$[T](feature: StructFeature[T]): T
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
$$[K, V](feature: MapFeature[K, V]): Map[K, V]
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
$$[T](feature: SetFeature[T]): Set[T]
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
$$[T](feature: ArrayFeature[T]): Array[T]
- Attributes
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- Definition Classes
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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
-
val
batchSize: IntParam
Batch size
Batch size
- Definition Classes
- GenericClassifierParams
-
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[_]): GenericREModel.this.type
- Definition Classes
- Params
-
def
clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()
-
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
-
val
datasetInfo: Param[String]
Descriptive information about the dataset being used.
Descriptive information about the dataset being used.
- Definition Classes
- GenericClassifierParams
-
final
def
defaultCopy[T <: Params](extra: ParamMap): T
- Attributes
- protected
- Definition Classes
- Params
-
def
dfAnnotate: UserDefinedFunction
- Definition Classes
- HasSimpleAnnotate
-
val
directionSensitive: BooleanParam
If it is
true
, only relations in the form of "ENTITY1-ENTITY2" will be considered, If it isfalse
, both "ENTITY1-ENTITY2" and "ENTITY2-ENTITY1" relations will be considered,If it is
true
, only relations in the form of "ENTITY1-ENTITY2" will be considered, If it isfalse
, both "ENTITY1-ENTITY2" and "ENTITY2-ENTITY1" relations will be considered,- Definition Classes
- RelationExtractionModel
-
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
-
val
dropout: FloatParam
Dropout coefficient
Dropout coefficient
- Definition Classes
- GenericClassifierParams
-
val
epochsN: IntParam
Maximum number of epochs to train
Maximum number of epochs to train
- Definition Classes
- GenericClassifierParams
-
final
def
eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
def
equals(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
def
explainParam(param: Param[_]): String
- Definition Classes
- Params
-
def
explainParams(): String
- Definition Classes
- Params
-
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
- GenericClassifierParams
-
val
features: ArrayBuffer[Feature[_, _, _]]
- Definition Classes
- HasFeatures
-
val
filterByTokenDistance: IntParam
filtering criterion based on number of token between entities.
filtering criterion based on number of token between entities. Model only finds relations that have fewer than the specified number of tokens between them.
- Definition Classes
- RelationExtractionModel
-
def
finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( classOf[java.lang.Throwable] )
-
val
fixImbalance: BooleanParam
Fix the imbalance in the training set by replicating examples of under represented categories
Fix the imbalance in the training set by replicating examples of under represented categories
- Definition Classes
- GenericClassifierParams
-
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
getBatchSize: Int
Batch size
Batch size
- Definition Classes
- GenericClassifierParams
-
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
-
def
getDatasetInfo: String
get descriptive information about the dataset being used
get descriptive information about the dataset being used
- Definition Classes
- GenericClassifierParams
-
final
def
getDefault[T](param: Param[T]): Option[T]
- Definition Classes
- Params
-
def
getDirectionSensitive: Boolean
Gets the directionSensitive
Gets the directionSensitive
- Definition Classes
- RelationExtractionModel
-
def
getDropout: Float
Dropout coefficient
Dropout coefficient
- Definition Classes
- GenericClassifierParams
-
def
getEncoder: GenericClassifierDataEncoder
- Definition Classes
- GenericClassifierModel
-
def
getFeatureScaling: String
Get feature scaling method
Get feature scaling method
- Definition Classes
- GenericClassifierParams
-
def
getFixImbalance: Boolean
Fix imbalance in training set
Fix imbalance in training set
- Definition Classes
- GenericClassifierParams
-
def
getInputCols: Array[String]
- Definition Classes
- HasInputAnnotationCols
-
def
getLabelColumn: String
Column with label per each document
Column with label per each document
- Definition Classes
- GenericClassifierParams
-
def
getLazyAnnotator: Boolean
- Definition Classes
- CanBeLazy
-
def
getLearningRate: Float
Learning Rate
Learning Rate
- Definition Classes
- GenericClassifierParams
-
def
getMaxEpochs: Int
Maximum number of epochs to train
Maximum number of epochs to train
- Definition Classes
- GenericClassifierParams
-
def
getMaxSyntacticDistance: Int
Maximal syntactic distance, as threshold (Default: 0)
Maximal syntactic distance, as threshold (Default: 0)
- Definition Classes
- RelationExtractionModel
-
def
getModelFile: String
Model file name
Model file name
- Definition Classes
- GenericClassifierParams
-
def
getMultiClass: Boolean
Gets the model multi class prediction mode
Gets the model multi class prediction mode
- Definition Classes
- GenericClassifierParams
-
final
def
getOrDefault[T](param: Param[T]): T
- Definition Classes
- Params
-
final
def
getOutputCol: String
- Definition Classes
- HasOutputAnnotationCol
-
def
getOutputLogsPath: String
Get output logs path
Get output logs path
- Definition Classes
- GenericClassifierParams
-
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
getScopeWindow: (Int, Int)
Get scope window
Get scope window
- Definition Classes
- RelationExtractionModel
-
def
getStorageRef: String
- Definition Classes
- HasStorageRef
-
def
getValidationSplit: Float
Choose the proportion of training dataset to be validated against the model on each Epoch.
Choose the proportion of training dataset to be validated against the model on each Epoch. The value should be between 0.0 and 1.0 and by default it is 0.0 and off.
- Definition Classes
- GenericClassifierParams
-
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
labelColumn: Param[String]
Column with label per each document
Column with label per each document
- Definition Classes
- GenericClassifierParams
-
val
lazyAnnotator: BooleanParam
- Definition Classes
- CanBeLazy
-
val
learningRate: FloatParam
Learning Rate
Learning Rate
- Definition Classes
- GenericClassifierParams
-
def
loadModel(sparkSession: SparkSession, tfModel: TensorflowWrapper, categories: Array[String], encoder: GenericClassifierDataEncoder, nerTags: Array[String]): GenericREModel.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
-
val
modelFile: Param[String]
Location of file of the model used for classification
Location of file of the model used for classification
- Definition Classes
- GenericClassifierParams
-
def
msgHelper(schema: StructType): String
- Attributes
- protected
- Definition Classes
- HasInputAnnotationCols
-
val
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
- GenericClassifierParams
-
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
-
val
outputLogsPath: Param[String]
Folder path to save training logs.
Folder path to save training logs. If no path is specified, the logs won't be stored in disk. The path can be a local file path, a distributed file path (HDFS, DBFS), or a cloud storage (S3).
- Definition Classes
- GenericClassifierParams
-
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
-
val
scopeWindow: IntArrayParam
The scope window of the feature generation for relations
The scope window of the feature generation for relations
- Definition Classes
- RelationExtractionModel
-
def
set[T](feature: StructFeature[T], value: T): GenericREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
set[K, V](feature: MapFeature[K, V], value: Map[K, V]): GenericREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
set[T](feature: SetFeature[T], value: Set[T]): GenericREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
set[T](feature: ArrayFeature[T], value: Array[T]): GenericREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
final
def
set(paramPair: ParamPair[_]): GenericREModel.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
set(param: String, value: Any): GenericREModel.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
set[T](param: Param[T], value: T): GenericREModel.this.type
- Definition Classes
- Params
-
def
setBatchSize(batch: Int): GenericREModel.this.type
Batch size
Batch size
- Definition Classes
- GenericClassifierParams
-
def
setCategoryNames(categoryNames: Array[String]): GenericREModel.this.type
- Definition Classes
- GenericClassifierModel
-
def
setCustomLabels(labels: HashMap[String, String]): GenericREModel.this.type
- Definition Classes
- RelationExtractionModel
-
def
setCustomLabels(labels: Map[String, String]): GenericREModel.this.type
Set custom relation labels
Set custom relation labels
- Definition Classes
- RelationExtractionModel
-
def
setDatasetInfo(value: String): GenericREModel.this.type
set descriptive information about the dataset being used
set descriptive information about the dataset being used
- Definition Classes
- GenericClassifierParams
-
def
setDefault[T](feature: StructFeature[T], value: () ⇒ T): GenericREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): GenericREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): GenericREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
def
setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): GenericREModel.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
-
final
def
setDefault(paramPairs: ParamPair[_]*): GenericREModel.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
setDefault[T](param: Param[T], value: T): GenericREModel.this.type
- Attributes
- protected[org.apache.spark.ml]
- Definition Classes
- Params
-
def
setDirectionSensitive(value: Boolean): GenericREModel.this.type
If it is
true
, only relations in the form of "ENTITY1-ENTITY2" will be considered, If it isfalse
, both "ENTITY1-ENTITY2" and "ENTITY2-ENTITY1" relations will be considered,If it is
true
, only relations in the form of "ENTITY1-ENTITY2" will be considered, If it isfalse
, both "ENTITY1-ENTITY2" and "ENTITY2-ENTITY1" relations will be considered,- Definition Classes
- RelationExtractionModel
-
def
setDoExceptionHandling(value: Boolean): GenericREModel.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
setDropout(dropout: Float): GenericREModel.this.type
Dropout coefficient
Dropout coefficient
- Definition Classes
- GenericClassifierParams
-
def
setEncoder(encoder: GenericClassifierDataEncoder): GenericREModel.this.type
- Definition Classes
- GenericClassifierModel
-
def
setEpochsNumber(epochs: Int): GenericREModel.this.type
Maximum number of epochs to train
Maximum number of epochs to train
- Definition Classes
- GenericClassifierParams
-
def
setFeatureScaling(featureScaling: String): GenericREModel.this.type
Set the feature scaling method.
Set the feature scaling method. Possible values are 'zscore', 'minmax' or empty (no scaling)
- Definition Classes
- GenericClassifierParams
-
def
setFilterByTokenDistance(value: Int): GenericREModel.this.type
filtering criterion based on number of token between entities.
filtering criterion based on number of token between entities. Model only finds relations that have fewer than the specified number of tokens between them
- Definition Classes
- RelationExtractionModel
-
def
setFixImbalance(fix: Boolean): GenericREModel.this.type
Fix imbalance of training set
Fix imbalance of training set
- Definition Classes
- GenericClassifierParams
-
final
def
setInputCols(value: String*): GenericREModel.this.type
- Definition Classes
- HasInputAnnotationCols
-
def
setInputCols(value: Array[String]): GenericREModel.this.type
- Definition Classes
- HasInputAnnotationCols
-
def
setLabelColumn(column: String): GenericREModel.this.type
Column with label per each document
Column with label per each document
- Definition Classes
- GenericClassifierParams
-
def
setLazyAnnotator(value: Boolean): GenericREModel.this.type
- Definition Classes
- CanBeLazy
-
def
setMaxSyntacticDistance(maxSyntacticDistance: Int): GenericREModel.this.type
Maximal syntactic distance, as threshold (Default: 0)
Maximal syntactic distance, as threshold (Default: 0)
- Definition Classes
- RelationExtractionModel
-
def
setModelFile(modelFile: String): GenericREModel.this.type
Set the model file name
Set the model file name
- Definition Classes
- GenericClassifierParams
-
def
setMultiClass(value: Boolean): GenericREModel.this.type
Sets the model in multi class prediction mode
Sets the model in multi class prediction mode
- Definition Classes
- GenericClassifierParams
-
final
def
setOutputCol(value: String): GenericREModel.this.type
- Definition Classes
- HasOutputAnnotationCol
-
def
setOutputLogsPath(outputLogsPath: String): GenericREModel.this.type
Set the output log path
Set the output log path
- Definition Classes
- GenericClassifierParams
-
def
setParent(parent: Estimator[GenericClassifierModel]): GenericClassifierModel
- Definition Classes
- Model
-
def
setPredictionThreshold(predictionThreshold: Float): GenericREModel.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]): GenericREModel.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): GenericREModel.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]]): GenericREModel.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]]): GenericREModel.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
setScopeWindow(window: (Int, Int)): GenericREModel.this.type
Sets the scope of the window of the feature generation for relations
Sets the scope of the window of the feature generation for relations
- Definition Classes
- RelationExtractionModel
-
def
setStorageRef(value: String): GenericREModel.this.type
- Definition Classes
- HasStorageRef
-
def
setTensorflowModel(spark: SparkSession, tf: TensorflowWrapper): GenericREModel.this.type
- Definition Classes
- GenericClassifierModel
-
def
setValidationSplit(validationSplit: Float): GenericREModel.this.type
Choose the proportion of training dataset to be validated against the model on each Epoch.
Choose the proportion of training dataset to be validated against the model on each Epoch. The value should be between 0.0 and 1.0 and by default it is 0.0 and off.
- Definition Classes
- GenericClassifierParams
-
def
setlearningRate(lr: Float): GenericREModel.this.type
Learning Rate
Learning Rate
- Definition Classes
- GenericClassifierParams
-
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
- 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
-
val
validationSplit: FloatParam
The proportion of training dataset to be used as validation set.
The proportion of training dataset to be used as validation set.
The model will be validated against this dataset on each Epoch and will not be used for training. The value should be between 0.0 and 1.0.
- Definition Classes
- GenericClassifierParams
-
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 RelationExtractionModel
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 GenericClassifierParams
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