class DrugNormalizer extends AnnotatorModel[DrugNormalizer] with HasSimpleAnnotate[DrugNormalizer] with CheckLicense
Annotator which normalizes raw text from clinical documents, e.g. scraped web pages or xml documents, from document type columns into Sentence. Removes all dirty characters from text following one or more input regex patterns. Can apply non wanted character removal which a specific policy. Can apply lower case normalization.
See Spark NLP Workshop for more examples of usage.
Example
val data = Seq( ("Sodium Chloride/Potassium Chloride 13bag"), ("interferon alfa-2b 10 million unit ( 1 ml ) injec"), ("aspirin 10 meq/ 5 ml oral sol") ).toDF("text") val document = new DocumentAssembler().setInputCol("text").setOutputCol("document") val drugNormalizer = new DrugNormalizer().setInputCols("document").setOutputCol("document_normalized") val trainingPipeline = new Pipeline().setStages(Array(document, drugNormalizer)) val result = trainingPipeline.fit(data).transform(data) result.selectExpr("explode(document_normalized.result) as normalized_text").show(false) +----------------------------------------------------+ |normalized_text | +----------------------------------------------------+ |Sodium Chloride / Potassium Chloride 13 bag | |interferon alfa - 2b 10000000 unt ( 1 ml ) injection| |aspirin 2 meq/ml oral solution | +----------------------------------------------------+
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def
_transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
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val
abbreviations: MapFeature[String, String]
abbreviation regex patterns which match will be extended in document
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def
afterAnnotate(dataset: DataFrame): DataFrame
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- AnnotatorModel
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def
annotate(annotations: Seq[Annotation]): Seq[Annotation]
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- DrugNormalizer → HasSimpleAnnotate
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final
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asInstanceOf[T0]: T0
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def
beforeAnnotate(dataset: Dataset[_]): Dataset[_]
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final
def
checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
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def
checkValidEnvironment(spark: Option[SparkSession], scopes: Seq[String]): Unit
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def
checkValidScope(scope: String): Unit
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def
checkValidScopeAndEnvironment(scope: String, spark: Option[SparkSession], checkLp: Boolean): Unit
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def
checkValidScopesAndEnvironment(scopes: Seq[String], spark: Option[SparkSession], checkLp: Boolean): Unit
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final
def
clear(param: Param[_]): DrugNormalizer.this.type
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clone(): AnyRef
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def
copy(extra: ParamMap): DrugNormalizer
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copyValues[T <: Params](to: T, extra: ParamMap): T
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defaultCopy[T <: Params](extra: ParamMap): T
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dfAnnotate: UserDefinedFunction
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explainParam(param: Param[_]): String
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explainParams(): String
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extraValidate(structType: StructType): Boolean
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extraValidateMsg: String
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extractParamMap(): ParamMap
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getClass(): Class[_]
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def
getDefault[T](param: Param[T]): Option[T]
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def
getInputCols: Array[String]
- Definition Classes
- HasInputAnnotationCols
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def
getLazyAnnotator: Boolean
- Definition Classes
- CanBeLazy
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def
getLowercase: Boolean
Lowercase tokens, default false
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final
def
getOrDefault[T](param: Param[T]): T
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final
def
getOutputCol: String
- Definition Classes
- HasOutputAnnotationCol
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def
getParam(paramName: String): Param[Any]
- Definition Classes
- Params
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def
getPolicy: String
Policy to remove patterns from text.
Policy to remove patterns from text. Defaults "all".
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final
def
hasDefault[T](param: Param[T]): Boolean
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hasParam(paramName: String): Boolean
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hasParent: Boolean
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def
initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
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def
initializeLogIfNecessary(isInterpreter: Boolean): Unit
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val
inputAnnotatorTypes: Array[AnnotatorType]
Input annotator type : DOCUMENT
Input annotator type : DOCUMENT
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- DrugNormalizer → HasInputAnnotationCols
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final
val
inputCols: StringArrayParam
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isTraceEnabled(): Boolean
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lazyAnnotator: BooleanParam
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def
log: Logger
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def
logDebug(msg: ⇒ String, throwable: Throwable): Unit
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def
logDebug(msg: ⇒ String): Unit
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logError(msg: ⇒ String, throwable: Throwable): Unit
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logError(msg: ⇒ String): Unit
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logInfo(msg: ⇒ String, throwable: Throwable): Unit
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logInfo(msg: ⇒ String): Unit
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logName: String
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logTrace(msg: ⇒ String, throwable: Throwable): Unit
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logTrace(msg: ⇒ String): Unit
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logWarning(msg: ⇒ String, throwable: Throwable): Unit
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logWarning(msg: ⇒ String): Unit
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val
lowercase: BooleanParam
whether to convert strings to lowercase (Default: false)
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def
msgHelper(schema: StructType): String
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def
onWrite(path: String, spark: SparkSession): Unit
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val
optionalInputAnnotatorTypes: Array[String]
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- HasInputAnnotationCols
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val
outputAnnotatorType: AnnotatorType
Output annotator type : DOCUMENT
Output annotator type : DOCUMENT
- Definition Classes
- DrugNormalizer → HasOutputAnnotatorType
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final
val
outputCol: Param[String]
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- HasOutputAnnotationCol
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lazy val
params: Array[Param[_]]
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var
parent: Estimator[DrugNormalizer]
- Definition Classes
- Model
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val
patterns: MapFeature[String, String]
normalization regex patterns which match will be normalized document
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val
policy: Param[String]
removalPolicy to remove patterns from text (Default: 'all')
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def
save(path: String): Unit
- Definition Classes
- MLWritable
- Annotations
- @Since( "1.6.0" ) @throws( ... )
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def
set[T](feature: StructFeature[T], value: T): DrugNormalizer.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
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def
set[K, V](feature: MapFeature[K, V], value: Map[K, V]): DrugNormalizer.this.type
- Attributes
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- Definition Classes
- HasFeatures
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def
set[T](feature: SetFeature[T], value: Set[T]): DrugNormalizer.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
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def
set[T](feature: ArrayFeature[T], value: Array[T]): DrugNormalizer.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
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final
def
set(paramPair: ParamPair[_]): DrugNormalizer.this.type
- Attributes
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final
def
set(param: String, value: Any): DrugNormalizer.this.type
- Attributes
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- Definition Classes
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final
def
set[T](param: Param[T], value: T): DrugNormalizer.this.type
- Definition Classes
- Params
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def
setDefault[T](feature: StructFeature[T], value: () ⇒ T): DrugNormalizer.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
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def
setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): DrugNormalizer.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
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def
setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): DrugNormalizer.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
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def
setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): DrugNormalizer.this.type
- Attributes
- protected
- Definition Classes
- HasFeatures
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final
def
setDefault(paramPairs: ParamPair[_]*): DrugNormalizer.this.type
- Attributes
- protected
- Definition Classes
- Params
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final
def
setDefault[T](param: Param[T], value: T): DrugNormalizer.this.type
- Attributes
- protected[org.apache.spark.ml]
- Definition Classes
- Params
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final
def
setInputCols(value: String*): DrugNormalizer.this.type
- Definition Classes
- HasInputAnnotationCols
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def
setInputCols(value: Array[String]): DrugNormalizer.this.type
- Definition Classes
- HasInputAnnotationCols
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def
setLazyAnnotator(value: Boolean): DrugNormalizer.this.type
- Definition Classes
- CanBeLazy
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def
setLowercase(value: Boolean): DrugNormalizer.this.type
Lower case tokens, default false
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final
def
setOutputCol(value: String): DrugNormalizer.this.type
- Definition Classes
- HasOutputAnnotationCol
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def
setParent(parent: Estimator[DrugNormalizer]): DrugNormalizer
- Definition Classes
- Model
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def
setPolicy(value: String): DrugNormalizer.this.type
Removal policy to apply.
Removal policy to apply. Valid policy values are: "all", "abbreviations", "dosages"
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final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
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def
toString(): String
- Definition Classes
- Identifiable → AnyRef → Any
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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()
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final
def
transformSchema(schema: StructType): StructType
- Definition Classes
- RawAnnotator → PipelineStage
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def
transformSchema(schema: StructType, logging: Boolean): StructType
- Attributes
- protected
- Definition Classes
- PipelineStage
- Annotations
- @DeveloperApi()
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val
uid: String
- Definition Classes
- DrugNormalizer → Identifiable
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def
validate(schema: StructType): Boolean
- Attributes
- protected
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- RawAnnotator
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
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- @throws( ... ) @native()
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def
wrapColumnMetadata(col: Column): Column
- Attributes
- protected
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- RawAnnotator
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def
write: MLWriter
- Definition Classes
- ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
Inherited from CheckLicense
Inherited from HasSimpleAnnotate[DrugNormalizer]
Inherited from AnnotatorModel[DrugNormalizer]
Inherited from CanBeLazy
Inherited from RawAnnotator[DrugNormalizer]
Inherited from HasOutputAnnotationCol
Inherited from HasInputAnnotationCols
Inherited from HasOutputAnnotatorType
Inherited from ParamsAndFeaturesWritable
Inherited from HasFeatures
Inherited from DefaultParamsWritable
Inherited from MLWritable
Inherited from Model[DrugNormalizer]
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