NerCrfApproach

Instance Constructors

new NerCrfApproach()
new NerCrfApproach(uid: String)

Type Members

type AnnotatorType = String

Definition Classes
HasAnnotatorType

Value Members

final def !=(arg0: Any): Boolean

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

Definition Classes
AnyRef → Any
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
protected
Definition Classes
HasFeatures
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
val annotatorType: String

Definition Classes
NerCrfApproach → HasAnnotatorType
final def asInstanceOf[T0]: T0

Definition Classes
Any
def beforeTraining(spark: SparkSession): Unit

Definition Classes
ApproachWithWordEmbeddings → AnnotatorApproach
val c0: IntParam
val caseSensitiveEmbeddings: BooleanParam

Definition Classes
HasEmbeddings
final def clear(param: Param[_]): NerCrfApproach.this.type

Definition Classes
Params
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
def close(): Unit

Definition Classes
HasEmbeddings → AutoCloseable
final def copy(extra: ParamMap): Estimator[NerCrfModel]

Definition Classes
AnnotatorApproach → Estimator → PipelineStage → Params
def copyValues[T <: Params](to: T, extra: ParamMap): T

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

Attributes
protected
Definition Classes
Params
val description: String

Definition Classes
NerCrfApproach → AnnotatorApproach
val embeddingsDim: IntParam

Definition Classes
HasEmbeddings
val embeddingsFormat: IntParam

Definition Classes
ApproachWithWordEmbeddings
val embeddingsRef: Param[String]

Definition Classes
HasEmbeddings
val entities: StringArrayParam

Definition Classes
NerApproach
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
val externalDataset: ExternalResourceParam

Definition Classes
NerApproach
val externalFeatures: ExternalResourceParam
def extraValidate(structType: StructType): Boolean

Attributes
protected
Definition Classes
AnnotatorApproach
def extraValidateMsg: String

Override for additional custom schema checks
Override for additional custom schema checks

Attributes
protected
Definition Classes
AnnotatorApproach
final def extractParamMap(): ParamMap

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

Definition Classes
Params
val features: ArrayBuffer[Feature[_, _, _]]

Definition Classes
HasFeatures
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def fit(dataset: Dataset[_]): NerCrfModel

Definition Classes
AnnotatorApproach → Estimator
def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[NerCrfModel]

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
def fit(dataset: Dataset[_], paramMap: ParamMap): NerCrfModel

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): NerCrfModel

Definition Classes
Estimator
Annotations
@Since( "2.0.0" ) @varargs()
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
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def getClusterEmbeddings: ClusterWordEmbeddings

Definition Classes
HasEmbeddings
final def getDefault[T](param: Param[T]): Option[T]

Definition Classes
Params
final def getInputCols: Array[String]

returns
input annotations columns currently used

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

Definition Classes
Params
final def getOutputCol: String

Gets annotation column name going to generate
Gets annotation column name going to generate

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

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

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

Definition Classes
Params
def hashCode(): Int

Definition Classes
AnyRef → Any
val includeEmbeddings: BooleanParam

Definition Classes
HasEmbeddings
def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

Attributes
protected
Definition Classes
Logging
def initializeLogIfNecessary(isInterpreter: Boolean): Unit

Attributes
protected
Definition Classes
Logging
final val inputCols: StringArrayParam

columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified
columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

Attributes
protected
Definition Classes
HasInputAnnotationCols
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 l2: DoubleParam
val labelColumn: Param[String]

Definition Classes
NerApproach
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
val lossEps: DoubleParam
val maxEpochs: IntParam

Definition Classes
NerApproach
val minEpochs: IntParam

Definition Classes
NerApproach
val minW: DoubleParam
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
def onTrained(model: NerCrfModel, spark: SparkSession): Unit

Definition Classes
ApproachWithWordEmbeddings → AnnotatorApproach
def onWrite(path: String, spark: SparkSession): Unit

Definition Classes
ParamsAndFeaturesWritable
final val outputCol: Param[String]

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

Definition Classes
Params
val randomSeed: IntParam

Definition Classes
NerApproach
final def recursiveFit(dataset: Dataset[_], recursivePipeline: PipelineModel): NerCrfModel

Definition Classes
HasRecursiveFit
val requiredAnnotatorTypes: Array[String]

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

Definition Classes
NerCrfApproach → HasInputAnnotationCols
def save(path: String): Unit

Definition Classes
MLWritable
Annotations
@Since( "1.6.0" ) @throws( ... )
def set[T](feature: StructFeature[T], value: T): NerCrfApproach.this.type

Attributes
protected
Definition Classes
HasFeatures
def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): NerCrfApproach.this.type

Attributes
protected
Definition Classes
HasFeatures
def set[T](feature: SetFeature[T], value: Set[T]): NerCrfApproach.this.type

Attributes
protected
Definition Classes
HasFeatures
def set[T](feature: ArrayFeature[T], value: Array[T]): NerCrfApproach.this.type

Attributes
protected
Definition Classes
HasFeatures
final def set(paramPair: ParamPair[_]): NerCrfApproach.this.type

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

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

Definition Classes
Params
def setC0(c0: Int): NerCrfApproach
def setCaseSensitiveEmbeddings(value: Boolean): NerCrfApproach.this.type

Definition Classes
HasEmbeddings
def setDefault[T](feature: StructFeature[T], value: () ⇒ T): NerCrfApproach.this.type

Attributes
protected
Definition Classes
HasFeatures
def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): NerCrfApproach.this.type

Attributes
protected
Definition Classes
HasFeatures
def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): NerCrfApproach.this.type

Attributes
protected
Definition Classes
HasFeatures
def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): NerCrfApproach.this.type

Attributes
protected
Definition Classes
HasFeatures
final def setDefault(paramPairs: ParamPair[_]*): NerCrfApproach.this.type

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

Attributes
protected
Definition Classes
Params
def setEmbeddingsDim(value: Int): NerCrfApproach.this.type

Definition Classes
HasEmbeddings
def setEmbeddingsRef(value: String): NerCrfApproach.this.type

Definition Classes
HasEmbeddings
def setEmbeddingsSource(path: String, nDims: Int, format: String): NerCrfApproach

Definition Classes
ApproachWithWordEmbeddings
def setEmbeddingsSource(path: String, nDims: Int, format: Format): NerCrfApproach

Definition Classes
ApproachWithWordEmbeddings
def setEntities(tags: Array[String]): NerCrfApproach

Definition Classes
NerApproach
def setExternalDataset(path: String, readAs: Format = ReadAs.LINE_BY_LINE, options: Map[String, String] = Map("format" -> "text")): NerCrfApproach.this.type

Definition Classes
NerApproach
def setExternalDataset(path: ExternalResource): NerCrfApproach

Definition Classes
NerApproach
def setExternalFeatures(path: String, delimiter: String, readAs: Format = ReadAs.LINE_BY_LINE, options: Map[String, String] = Map("format" -> "text")): NerCrfApproach.this.type
def setExternalFeatures(value: ExternalResource): NerCrfApproach
def setIncludeEmbeddings(value: Boolean): NerCrfApproach.this.type

Definition Classes
HasEmbeddings
final def setInputCols(value: String*): NerCrfApproach.this.type

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

Overrides required annotators column if different than default
Overrides required annotators column if different than default

Definition Classes
HasInputAnnotationCols
def setL2(l2: Double): NerCrfApproach
def setLabelColumn(column: String): NerCrfApproach

Definition Classes
NerApproach
def setLossEps(eps: Double): NerCrfApproach
def setMaxEpochs(epochs: Int): NerCrfApproach

Definition Classes
NerApproach
def setMinEpochs(epochs: Int): NerCrfApproach

Definition Classes
NerApproach
def setMinW(w: Double): NerCrfApproach
final def setOutputCol(value: String): NerCrfApproach.this.type

Overrides annotation column name when transforming
Overrides annotation column name when transforming

Definition Classes
HasOutputAnnotationCol
def setRandomSeed(seed: Int): NerCrfApproach

Definition Classes
NerApproach
def setVerbose(verbose: Level): NerCrfApproach

Definition Classes
NerApproach
def setVerbose(verbose: Int): NerCrfApproach

Definition Classes
NerApproach
val sourceEmbeddingsPath: Param[String]

Definition Classes
ApproachWithWordEmbeddings
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
Identifiable → AnyRef → Any
def train(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): NerCrfModel

Definition Classes
NerCrfApproach → AnnotatorApproach
final def transformSchema(schema: StructType): StructType

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

Definition Classes
AnnotatorApproach → PipelineStage
def transformSchema(schema: StructType, logging: Boolean): StructType

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

Definition Classes
NerCrfApproach → Identifiable
def validate(schema: StructType): Boolean

takes a Dataset and checks to see if all the required annotation types are present.
takes a Dataset and checks to see if all the required annotation types are present.
schema
to be validated
returns
True if all the required types are present, else false

Attributes
protected
Definition Classes
HasInputAnnotationCols
val verbose: IntParam

Definition Classes
NerApproach
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( ... )
def write: MLWriter

Definition Classes
ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable

Related Docs: object NerCrfApproach | package crf

class NerCrfApproach extends ApproachWithWordEmbeddings[NerCrfApproach, NerCrfModel] with HasRecursiveFit[NerCrfModel] with NerApproach[NerCrfApproach]

Instance Constructors

new NerCrfApproach()

new NerCrfApproach(uid: String)

Type Members

type AnnotatorType = String

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def $[T](param: Param[T]): T

def $$[T](feature: StructFeature[T]): T

def $$[K, V](feature: MapFeature[K, V]): Map[K, V]

def $$[T](feature: SetFeature[T]): Set[T]

def $$[T](feature: ArrayFeature[T]): Array[T]

final def ==(arg0: Any): Boolean

val annotatorType: String

final def asInstanceOf[T0]: T0

def beforeTraining(spark: SparkSession): Unit

val c0: IntParam

val caseSensitiveEmbeddings: BooleanParam

final def clear(param: Param[_]): NerCrfApproach.this.type

def clone(): AnyRef

def close(): Unit

final def copy(extra: ParamMap): Estimator[NerCrfModel]

def copyValues[T <: Params](to: T, extra: ParamMap): T

final def defaultCopy[T <: Params](extra: ParamMap): T

val description: String

val embeddingsDim: IntParam

val embeddingsFormat: IntParam

val embeddingsRef: Param[String]

val entities: StringArrayParam

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def explainParam(param: Param[_]): String

def explainParams(): String

val externalDataset: ExternalResourceParam

val externalFeatures: ExternalResourceParam

def extraValidate(structType: StructType): Boolean

def extraValidateMsg: String

final def extractParamMap(): ParamMap

final def extractParamMap(extra: ParamMap): ParamMap

val features: ArrayBuffer[Feature[_, _, _]]

def finalize(): Unit

final def fit(dataset: Dataset[_]): NerCrfModel

def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[NerCrfModel]

def fit(dataset: Dataset[_], paramMap: ParamMap): NerCrfModel

def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): NerCrfModel

def get[T](feature: StructFeature[T]): Option[T]

def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]

def get[T](feature: SetFeature[T]): Option[Set[T]]

def get[T](feature: ArrayFeature[T]): Option[Array[T]]

final def get[T](param: Param[T]): Option[T]

final def getClass(): Class[_]

def getClusterEmbeddings: ClusterWordEmbeddings

final def getDefault[T](param: Param[T]): Option[T]

final def getInputCols: Array[String]

final def getOrDefault[T](param: Param[T]): T

final def getOutputCol: String

def getParam(paramName: String): Param[Any]

final def hasDefault[T](param: Param[T]): Boolean

def hasParam(paramName: String): Boolean

def hashCode(): Int

val includeEmbeddings: BooleanParam

def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

final val inputCols: StringArrayParam

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

final def isInstanceOf[T0]: Boolean

final def isSet(param: Param[_]): Boolean

def isTraceEnabled(): Boolean

val l2: DoubleParam

val labelColumn: Param[String]

def log: Logger

def logDebug(msg: ⇒ String, throwable: Throwable): Unit

def logDebug(msg: ⇒ String): Unit

def logError(msg: ⇒ String, throwable: Throwable): Unit

def logError(msg: ⇒ String): Unit

def logInfo(msg: ⇒ String, throwable: Throwable): Unit