Packages

package explainers

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Type Members

  1. trait CanValidateSchema extends AnyRef
  2. trait HasBackgroundData extends Params with CanValidateSchema
  3. trait HasExplainTarget extends Params with CanValidateSchema
  4. trait HasMetricsCol extends Params with CanValidateSchema
  5. trait HasModel extends Params with CanValidateSchema
  6. trait HasNumSamples extends Params with CanValidateSchema
  7. trait HasSamplingFraction extends Params with CanValidateSchema
  8. trait HasSuperpixelCol extends Params with CanValidateSchema
  9. trait HasTokensCol extends Params with CanValidateSchema
  10. trait ImageExplainer extends AnyRef

    Common preprocessing logic for image explainers

  11. class ImageLIME extends LIMEBase with ImageLIMEParams with ImageExplainer
  12. trait ImageLIMEParams extends LIMEParams with HasSamplingFraction with HasCellSize with HasModifier with HasInputCol with HasSuperpixelCol
  13. class ImageSHAP extends KernelSHAPBase with ImageSHAPParams with ImageExplainer
  14. trait ImageSHAPParams extends KernelSHAPParams with HasCellSize with HasModifier with HasInputCol with HasSuperpixelCol
  15. abstract class KernelSHAPBase extends Transformer with LocalExplainer with KernelSHAPParams with Wrappable with BasicLogging
  16. trait KernelSHAPParams extends HasNumSamples with HasMetricsCol
  17. abstract class LIMEBase extends Transformer with LocalExplainer with LIMEParams with Wrappable with BasicLogging
  18. trait LIMEParams extends HasNumSamples with HasMetricsCol
  19. final class LassoRegression extends RegressionBase
  20. final class LeastSquaresRegression extends RegressionBase
  21. trait LocalExplainer extends Transformer with HasExplainTarget with HasOutputCol with HasModel with ComplexParamsWritable
  22. abstract class RegressionBase extends AnyRef

    The RegressionBase class centers and rescales the input matrix and output vector to support fitting intercept and specifying sampleWeights.

    The RegressionBase class centers and rescales the input matrix and output vector to support fitting intercept and specifying sampleWeights. The underlying regression algorithm does not need to support fitting intercept and sample weights.

  23. case class RegressionResult(coefficients: DenseVector[Double], intercept: Double, rSquared: Double, loss: Double) extends (DenseVector[Double]) ⇒ Double with Product with Serializable
  24. class TabularLIME extends LIMEBase with HasInputCols with HasBackgroundData
  25. class TabularSHAP extends KernelSHAPBase with HasInputCols with HasBackgroundData
  26. trait TextExplainer extends AnyRef

    Common preprocessing logic for text explainers

  27. class TextLIME extends LIMEBase with TextLIMEParams with TextExplainer
  28. trait TextLIMEParams extends LIMEParams with HasSamplingFraction with HasInputCol with HasTokensCol
  29. class TextSHAP extends KernelSHAPBase with TextSHAPParams with TextExplainer
  30. trait TextSHAPParams extends KernelSHAPParams with HasInputCol with HasTokensCol
  31. class VectorLIME extends LIMEBase with HasInputCol with HasBackgroundData
  32. class VectorSHAP extends KernelSHAPBase with HasInputCol with HasBackgroundData

Value Members

  1. object ImageLIME extends ComplexParamsReadable[ImageLIME] with Serializable
  2. object ImageSHAP extends ComplexParamsReadable[ImageSHAP] with Serializable
  3. object KernelSHAPBase extends Serializable
  4. object LocalExplainer extends Serializable
  5. object TabularLIME extends ComplexParamsReadable[TabularLIME] with Serializable
  6. object TabularSHAP extends ComplexParamsReadable[TabularSHAP] with Serializable
  7. object TextLIME extends ComplexParamsReadable[TextLIME] with Serializable
  8. object TextSHAP extends ComplexParamsReadable[TextSHAP] with Serializable
  9. object VectorLIME extends ComplexParamsReadable[VectorLIME] with Serializable
  10. object VectorSHAP extends ComplexParamsReadable[VectorSHAP] with Serializable

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