Packages

class ImageLIME extends Transformer with LIMEBase with Wrappable with HasModifier with HasCellSize with BasicLogging

Distributed implementation of Local Interpretable Model-Agnostic Explanations (LIME)

https://arxiv.org/pdf/1602.04938v1.pdf

Annotations
@deprecated
Deprecated

(Since version 1.0.0-rc3) Please use 'com.microsoft.azure.synapse.ml.explainers.ImageLIME'.

Linear Supertypes
BasicLogging, HasCellSize, HasModifier, Wrappable, RWrappable, PythonWrappable, BaseWrappable, LIMEBase, ComplexParamsWritable, MLWritable, LIMEParams, HasPredictionCol, HasOutputCol, HasInputCol, Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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  2. By Inheritance
Inherited
  1. ImageLIME
  2. BasicLogging
  3. HasCellSize
  4. HasModifier
  5. Wrappable
  6. RWrappable
  7. PythonWrappable
  8. BaseWrappable
  9. LIMEBase
  10. ComplexParamsWritable
  11. MLWritable
  12. LIMEParams
  13. HasPredictionCol
  14. HasOutputCol
  15. HasInputCol
  16. Transformer
  17. PipelineStage
  18. Logging
  19. Params
  20. Serializable
  21. Serializable
  22. Identifiable
  23. AnyRef
  24. Any
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Visibility
  1. Public
  2. All

Instance Constructors

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

Value Members

  1. val cellSize: DoubleParam
    Definition Classes
    HasCellSize
  2. final def clear(param: Param[_]): ImageLIME.this.type
    Definition Classes
    Params
  3. def copy(extra: ParamMap): Transformer
    Definition Classes
    ImageLIME → Transformer → PipelineStage → Params
  4. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  5. def explainParams(): String
    Definition Classes
    Params
  6. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  7. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  8. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  9. def getCellSize: Double
    Definition Classes
    HasCellSize
  10. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  11. def getInputCol: String

    Definition Classes
    HasInputCol
  12. def getModel: Transformer
    Definition Classes
    LIMEParams
  13. def getModifier: Double
    Definition Classes
    HasModifier
  14. def getNSamples: Int
    Definition Classes
    LIMEParams
  15. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  16. def getOutputCol: String

    Definition Classes
    HasOutputCol
  17. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  18. final def getPredictionCol: String
    Definition Classes
    HasPredictionCol
  19. def getRegularization: Double
    Definition Classes
    LIMEParams
  20. def getSamplingFraction: Double
    Definition Classes
    LIMEParams
  21. def getSuperpixelCol: String
  22. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  23. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  24. val inputCol: Param[String]

    The name of the input column

    The name of the input column

    Definition Classes
    HasInputCol
  25. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  26. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  27. def logClass(): Unit
    Definition Classes
    BasicLogging
  28. def logFit[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  29. def logPredict[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  30. def logTrain[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  31. def logTransform[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  32. def logVerb[T](verb: String, f: ⇒ T): T
    Definition Classes
    BasicLogging
  33. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  34. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  35. val model: TransformerParam
    Definition Classes
    LIMEParams
  36. val modifier: DoubleParam
    Definition Classes
    HasModifier
  37. val nSamples: IntParam
    Definition Classes
    LIMEParams
  38. val outputCol: Param[String]

    The name of the output column

    The name of the output column

    Definition Classes
    HasOutputCol
  39. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  40. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  41. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  42. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  43. val regularization: DoubleParam
    Definition Classes
    LIMEParams
  44. val samplingFraction: DoubleParam
    Definition Classes
    LIMEParams
  45. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  46. final def set[T](param: Param[T], value: T): ImageLIME.this.type
    Definition Classes
    Params
  47. def setCellSize(v: Double): ImageLIME.this.type
    Definition Classes
    HasCellSize
  48. def setInputCol(value: String): ImageLIME.this.type

    Definition Classes
    HasInputCol
  49. def setModel(v: Transformer): ImageLIME.this.type
    Definition Classes
    LIMEParams
  50. def setModifier(v: Double): ImageLIME.this.type
    Definition Classes
    HasModifier
  51. def setNSamples(v: Int): ImageLIME.this.type
    Definition Classes
    LIMEParams
  52. def setOutputCol(value: String): ImageLIME.this.type

    Definition Classes
    HasOutputCol
  53. def setPredictionCol(v: String): ImageLIME.this.type
    Definition Classes
    LIMEParams
  54. def setRegularization(v: Double): ImageLIME.this.type
    Definition Classes
    LIMEParams
  55. def setSamplingFraction(d: Double): ImageLIME.this.type
    Definition Classes
    LIMEParams
  56. def setSuperpixelCol(v: String): ImageLIME.this.type
  57. val superpixelCol: Param[String]
  58. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  59. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    ImageLIME → Transformer
  60. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  61. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  62. def transformSchema(schema: StructType): StructType
    Definition Classes
    ImageLIME → PipelineStage
  63. val uid: String
    Definition Classes
    ImageLIME → BasicLogging → Identifiable
  64. val ver: String
    Definition Classes
    BasicLogging
  65. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable