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c

net.sansa_stack.ml.spark.utils

FeatureExtractorModel

class FeatureExtractorModel extends Transformer

This class creates from a dataset of triples a feature representing dataframe which is needed for steps like spark mllib countVect

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Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. FeatureExtractorModel
  2. Transformer
  3. PipelineStage
  4. Logging
  5. Params
  6. Serializable
  7. Serializable
  8. Identifiable
  9. AnyRef
  10. Any
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Visibility
  1. Public
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Instance Constructors

  1. new FeatureExtractorModel()

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. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. final def clear(param: Param[_]): FeatureExtractorModel.this.type
    Definition Classes
    Params
  7. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native() @IntrinsicCandidate()
  8. def copy(extra: ParamMap): Transformer
    Definition Classes
    FeatureExtractorModel → Transformer → PipelineStage → Params
  9. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  10. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  11. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  12. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  13. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  14. def explainParams(): String
    Definition Classes
    Params
  15. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  16. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  17. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  18. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @IntrinsicCandidate()
  19. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  20. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  21. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  22. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  23. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  24. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @IntrinsicCandidate()
  25. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  26. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  27. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  28. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  29. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  30. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  31. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  32. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  33. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  34. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  35. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  36. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  37. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  38. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  39. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  40. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  41. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  42. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  43. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  44. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @IntrinsicCandidate()
  45. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @IntrinsicCandidate()
  46. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  47. final def set(paramPair: ParamPair[_]): FeatureExtractorModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  48. final def set(param: String, value: Any): FeatureExtractorModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  49. final def set[T](param: Param[T], value: T): FeatureExtractorModel.this.type
    Definition Classes
    Params
  50. final def setDefault(paramPairs: ParamPair[_]*): FeatureExtractorModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  51. final def setDefault[T](param: Param[T], value: T): FeatureExtractorModel.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  52. def setMode(mode: String): FeatureExtractorModel.this.type

    This method changes the methodology how we flat our graph to get from each URI the desired feature

    This method changes the methodology how we flat our graph to get from each URI the desired feature

    mode

    a string specifying the modes. moders are abbreviations like "at" for all triples

    returns

    return da dataframe with two columns one for the string of a respective URI and one for the feature vector al list of strings

  53. def setOutputCol(colName: String): FeatureExtractorModel.this.type
  54. val spark: SparkSession
  55. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  56. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  57. def transform(triples: RDD[Triple]): DataFrame

    this is the alternative transform when you read in rdd of triple of jena node over sansa rdf

    this is the alternative transform when you read in rdd of triple of jena node over sansa rdf

    triples

    rdd of triple of jena node

    returns

    a dataframe with two columns, one for string of URI and one of a list of string based features

  58. def transform(dataset: Dataset[_]): DataFrame

    takes read in dataframe and produces a dataframe with features

    takes read in dataframe and produces a dataframe with features

    dataset

    most likely a dataframe read in over sansa rdf layer

    returns

    a dataframe with two columns, one for string of URI and one of a list of string based features

    Definition Classes
    FeatureExtractorModel → Transformer
  59. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  60. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  61. def transformSchema(schema: StructType): StructType
    Definition Classes
    FeatureExtractorModel → PipelineStage
  62. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  63. val uid: String
    Definition Classes
    FeatureExtractorModel → Identifiable
  64. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  65. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  66. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] ) @Deprecated
    Deprecated

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

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