class TabularLIME extends LIMEBase with HasInputCols with HasBackgroundData

Linear Supertypes
HasBackgroundData, HasInputCols, LIMEBase, SynapseMLLogging, Wrappable, DotnetWrappable, RWrappable, PythonWrappable, BaseWrappable, LIMEParams, HasMetricsCol, HasNumSamples, LocalExplainer, ComplexParamsWritable, MLWritable, HasModel, HasOutputCol, HasExplainTarget, CanValidateSchema, Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. TabularLIME
  2. HasBackgroundData
  3. HasInputCols
  4. LIMEBase
  5. SynapseMLLogging
  6. Wrappable
  7. DotnetWrappable
  8. RWrappable
  9. PythonWrappable
  10. BaseWrappable
  11. LIMEParams
  12. HasMetricsCol
  13. HasNumSamples
  14. LocalExplainer
  15. ComplexParamsWritable
  16. MLWritable
  17. HasModel
  18. HasOutputCol
  19. HasExplainTarget
  20. CanValidateSchema
  21. Transformer
  22. PipelineStage
  23. Logging
  24. Params
  25. Serializable
  26. Serializable
  27. Identifiable
  28. AnyRef
  29. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new TabularLIME()
  2. new TabularLIME(uid: String)

Value Members

  1. final val backgroundData: DataFrameParam
    Definition Classes
    HasBackgroundData
  2. val categoricalFeatures: StringArrayParam
  3. final def clear(param: Param[_]): TabularLIME.this.type
    Definition Classes
    Params
  4. def copy(extra: ParamMap): Transformer
    Definition Classes
    LIMEBase → Transformer → PipelineStage → Params
  5. def dotnetAdditionalMethods: String
    Definition Classes
    DotnetWrappable
  6. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  7. def explainParams(): String
    Definition Classes
    Params
  8. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  9. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  10. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  11. final def getBackgroundData: DataFrame
    Definition Classes
    HasBackgroundData
  12. def getCategoricalFeatures: Array[String]
  13. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  14. final def getInputCols: Array[String]
    Definition Classes
    HasInputCols
  15. def getKernelWidth: Double
    Definition Classes
    LIMEParams
  16. final def getMetricsCol: String
    Definition Classes
    HasMetricsCol
  17. final def getModel: Transformer
    Definition Classes
    HasModel
  18. final def getNumSamples: Int
    Definition Classes
    HasNumSamples
  19. final def getNumSamplesOpt: Option[Int]
    Definition Classes
    HasNumSamples
  20. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  21. final def getOutputCol: String
    Definition Classes
    HasOutputCol
  22. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  23. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  24. def getRegularization: Double
    Definition Classes
    LIMEParams
  25. final def getTargetClasses: Array[Int]
    Definition Classes
    HasExplainTarget
  26. final def getTargetClassesCol: String
    Definition Classes
    HasExplainTarget
  27. final def getTargetCol: String
    Definition Classes
    HasExplainTarget
  28. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  29. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  30. final val inputCols: StringArrayParam
    Definition Classes
    HasInputCols
  31. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  32. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  33. val kernelWidth: DoubleParam
    Definition Classes
    LIMEParams
  34. def logClass(): Unit
    Definition Classes
    SynapseMLLogging
  35. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  36. def logTrain[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  37. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  38. def logVerb[T](verb: String, f: ⇒ T, columns: Int = -1): T
    Definition Classes
    SynapseMLLogging
  39. def makeDotnetFile(conf: CodegenConfig): Unit
    Definition Classes
    DotnetWrappable
  40. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  41. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  42. final val metricsCol: Param[String]
    Definition Classes
    HasMetricsCol
  43. final val model: TransformerParam
    Definition Classes
    HasModel
  44. final val numSamples: IntParam
    Definition Classes
    HasNumSamples
  45. final val outputCol: Param[String]
    Definition Classes
    HasOutputCol
  46. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  47. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  48. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  49. val regularization: DoubleParam
    Definition Classes
    LIMEParams
  50. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  51. final def set[T](param: Param[T], value: T): TabularLIME.this.type
    Definition Classes
    Params
  52. final def setBackgroundData(value: DataFrame): TabularLIME.this.type
    Definition Classes
    HasBackgroundData
  53. def setCategoricalFeatures(values: Array[String]): TabularLIME.this.type
  54. def setInputCols(values: Array[String]): TabularLIME.this.type
  55. def setKernelWidth(v: Double): TabularLIME.this.type
    Definition Classes
    LIMEParams
  56. final def setMetricsCol(v: String): TabularLIME.this.type
    Definition Classes
    HasMetricsCol
  57. final def setModel(v: Transformer): TabularLIME.this.type
    Definition Classes
    HasModel
  58. final def setNumSamples(value: Int): TabularLIME.this.type
    Definition Classes
    HasNumSamples
  59. final def setOutputCol(value: String): TabularLIME.this.type
    Definition Classes
    LocalExplainer
  60. def setRegularization(v: Double): TabularLIME.this.type
    Definition Classes
    LIMEParams
  61. final def setTargetClasses(values: Array[Int]): TabularLIME.this.type
    Definition Classes
    HasExplainTarget
  62. final def setTargetClassesCol(value: String): TabularLIME.this.type
    Definition Classes
    HasExplainTarget
  63. final def setTargetCol(value: String): TabularLIME.this.type
    Definition Classes
    HasExplainTarget
  64. final val targetClasses: IntArrayParam
    Definition Classes
    HasExplainTarget
  65. final val targetClassesCol: Param[String]
    Definition Classes
    HasExplainTarget
  66. final val targetCol: Param[String]
    Definition Classes
    HasExplainTarget
  67. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  68. final def transform(instances: Dataset[_]): DataFrame
    Definition Classes
    LIMEBase → Transformer
  69. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  70. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  71. def transformSchema(schema: StructType): StructType
    Definition Classes
    LIMEBase → LocalExplainer → PipelineStage
  72. val uid: String
    Definition Classes
    TabularLIME → LIMEBase → SynapseMLLogging → Identifiable
  73. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable