VectorLIME implements VectorLIME More...

Inheritance diagram for Synapse.ML.Explainers.VectorLIME:

Collaboration diagram for Synapse.ML.Explainers.VectorLIME:

Public Member Functions
	VectorLIME ()
	Creates a VectorLIME without any parameters. More...

	VectorLIME (string uid)
	Creates a VectorLIME with a UID that is used to give the VectorLIME a unique ID. More...

VectorLIME	SetBackgroundData (DataFrame value)
	Sets value for backgroundData More...

VectorLIME	SetInputCol (string value)
	Sets value for inputCol More...

VectorLIME	SetKernelWidth (double value)
	Sets value for kernelWidth More...

VectorLIME	SetMetricsCol (string value)
	Sets value for metricsCol More...

VectorLIME	SetModel (JavaTransformer value)
	Sets value for model More...

VectorLIME	SetNumSamples (int value)
	Sets value for numSamples More...

VectorLIME	SetOutputCol (string value)
	Sets value for outputCol More...

VectorLIME	SetRegularization (double value)
	Sets value for regularization More...

VectorLIME	SetTargetClasses (int[] value)
	Sets value for targetClasses More...

VectorLIME	SetTargetClassesCol (string value)
	Sets value for targetClassesCol More...

VectorLIME	SetTargetCol (string value)
	Sets value for targetCol More...

DataFrame	GetBackgroundData ()
	Gets backgroundData value More...

string	GetInputCol ()
	Gets inputCol value More...

double	GetKernelWidth ()
	Gets kernelWidth value More...

string	GetMetricsCol ()
	Gets metricsCol value More...

JavaTransformer	GetModel ()
	Gets model value More...

int	GetNumSamples ()
	Gets numSamples value More...

string	GetOutputCol ()
	Gets outputCol value More...

double	GetRegularization ()
	Gets regularization value More...

int []	GetTargetClasses ()
	Gets targetClasses value More...

string	GetTargetClassesCol ()
	Gets targetClassesCol value More...

string	GetTargetCol ()
	Gets targetCol value More...

void	Save (string path)
	Saves the object so that it can be loaded later using Load. Note that these objects can be shared with Scala by Loading or Saving in Scala. More...

JavaMLWriter	Write ()
	Returns a JavaMLWriter instance for this ML instance.

JavaMLReader< VectorLIME >	Read ()
	Get the corresponding JavaMLReader instance. More...

Static Public Member Functions
static VectorLIME	Load (string path)
	Loads the VectorLIME that was previously saved using Save(string). More...

Detailed Description

VectorLIME implements VectorLIME

Constructor & Destructor Documentation

◆ VectorLIME() [1/2]

Synapse.ML.Explainers.VectorLIME.VectorLIME ( )

inline

Creates a VectorLIME without any parameters.

◆ VectorLIME() [2/2]

Synapse.ML.Explainers.VectorLIME.VectorLIME ( string uid )

inline

Creates a VectorLIME with a UID that is used to give the VectorLIME a unique ID.

Parameters

uid	An immutable unique ID for the object and its derivatives.

Member Function Documentation

◆ GetBackgroundData()

DataFrame Synapse.ML.Explainers.VectorLIME.GetBackgroundData ( )

Gets backgroundData value

Returns: backgroundData: A dataframe containing background data

◆ GetInputCol()

string Synapse.ML.Explainers.VectorLIME.GetInputCol ( )

Gets inputCol value

Returns: inputCol: input column name

◆ GetKernelWidth()

double Synapse.ML.Explainers.VectorLIME.GetKernelWidth ( )

Gets kernelWidth value

Returns: kernelWidth: Kernel width. Default value: sqrt (number of features) * 0.75

◆ GetMetricsCol()

string Synapse.ML.Explainers.VectorLIME.GetMetricsCol ( )

Gets metricsCol value

Returns: metricsCol: Column name for fitting metrics

◆ GetModel()

JavaTransformer Synapse.ML.Explainers.VectorLIME.GetModel ( )

inline

Gets model value

Returns: model: The model to be interpreted.

◆ GetNumSamples()

int Synapse.ML.Explainers.VectorLIME.GetNumSamples ( )

Gets numSamples value

Returns: numSamples: Number of samples to generate.

◆ GetOutputCol()

string Synapse.ML.Explainers.VectorLIME.GetOutputCol ( )

Gets outputCol value

Returns: outputCol: output column name

◆ GetRegularization()

double Synapse.ML.Explainers.VectorLIME.GetRegularization ( )

Gets regularization value

Returns: regularization: Regularization param for the lasso. Default value: 0.

◆ GetTargetClasses()

int [] Synapse.ML.Explainers.VectorLIME.GetTargetClasses ( )

Gets targetClasses value

Returns: targetClasses: The indices of the classes for multinomial classification models. Default: 0.For regression models this parameter is ignored.

◆ GetTargetClassesCol()

string Synapse.ML.Explainers.VectorLIME.GetTargetClassesCol ( )

Gets targetClassesCol value

Returns: targetClassesCol: The name of the column that specifies the indices of the classes for multinomial classification models.

◆ GetTargetCol()

string Synapse.ML.Explainers.VectorLIME.GetTargetCol ( )

Gets targetCol value

Returns: targetCol: The column name of the prediction target to explain (i.e. the response variable). This is usually set to "prediction" for regression models and "probability" for probabilistic classification models. Default value: probability

◆ Load()

static VectorLIME Synapse.ML.Explainers.VectorLIME.Load ( string path )

static

Loads the VectorLIME that was previously saved using Save(string).

Parameters

path	The path the previous VectorLIME was saved to

Returns: New VectorLIME object, loaded from path.

◆ Read()

JavaMLReader<VectorLIME> Synapse.ML.Explainers.VectorLIME.Read ( )

Get the corresponding JavaMLReader instance.

Returns: an JavaMLReader<VectorLIME> instance for this ML instance.

◆ Save()

void Synapse.ML.Explainers.VectorLIME.Save ( string path )

Saves the object so that it can be loaded later using Load. Note that these objects can be shared with Scala by Loading or Saving in Scala.

Parameters

path	The path to save the object to

◆ SetBackgroundData()

VectorLIME Synapse.ML.Explainers.VectorLIME.SetBackgroundData ( DataFrame value )

Sets value for backgroundData

Parameters

value A dataframe containing background data

Returns: New VectorLIME object

◆ SetInputCol()

VectorLIME Synapse.ML.Explainers.VectorLIME.SetInputCol ( string value )

Sets value for inputCol

Parameters

value input column name

Returns: New VectorLIME object

◆ SetKernelWidth()

VectorLIME Synapse.ML.Explainers.VectorLIME.SetKernelWidth ( double value )

Sets value for kernelWidth

Parameters

value Kernel width. Default value: sqrt (number of features) * 0.75

Returns: New VectorLIME object

◆ SetMetricsCol()

VectorLIME Synapse.ML.Explainers.VectorLIME.SetMetricsCol ( string value )

Sets value for metricsCol

Parameters

value Column name for fitting metrics

Returns: New VectorLIME object

◆ SetModel()

VectorLIME Synapse.ML.Explainers.VectorLIME.SetModel ( JavaTransformer value )

Sets value for model

Parameters

value The model to be interpreted.

Returns: New VectorLIME object

◆ SetNumSamples()

VectorLIME Synapse.ML.Explainers.VectorLIME.SetNumSamples ( int value )

Sets value for numSamples

Parameters

value Number of samples to generate.

Returns: New VectorLIME object

◆ SetOutputCol()

VectorLIME Synapse.ML.Explainers.VectorLIME.SetOutputCol ( string value )

Sets value for outputCol

Parameters

value output column name

Returns: New VectorLIME object

◆ SetRegularization()

VectorLIME Synapse.ML.Explainers.VectorLIME.SetRegularization ( double value )

Sets value for regularization

Parameters

value Regularization param for the lasso. Default value: 0.

Returns: New VectorLIME object

◆ SetTargetClasses()

VectorLIME Synapse.ML.Explainers.VectorLIME.SetTargetClasses ( int [] value )

Sets value for targetClasses

Parameters

value The indices of the classes for multinomial classification models. Default: 0.For regression models this parameter is ignored.

Returns: New VectorLIME object

◆ SetTargetClassesCol()

VectorLIME Synapse.ML.Explainers.VectorLIME.SetTargetClassesCol ( string value )

Sets value for targetClassesCol

Parameters

value The name of the column that specifies the indices of the classes for multinomial classification models.

Returns: New VectorLIME object

◆ SetTargetCol()

VectorLIME Synapse.ML.Explainers.VectorLIME.SetTargetCol ( string value )

Sets value for targetCol

Parameters

value The column name of the prediction target to explain (i.e. the response variable). This is usually set to "prediction" for regression models and "probability" for probabilistic classification models. Default value: probability

Returns: New VectorLIME object

The documentation for this class was generated from the following file:

synapse/ml/explainers/VectorLIME.cs

Public Member Functions

Static Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ VectorLIME() [1/2]

◆ VectorLIME() [2/2]

Member Function Documentation

◆ GetBackgroundData()

◆ GetInputCol()

◆ GetKernelWidth()

◆ GetMetricsCol()

◆ GetModel()

◆ GetNumSamples()

◆ GetOutputCol()

◆ GetRegularization()

◆ GetTargetClasses()

◆ GetTargetClassesCol()

◆ GetTargetCol()

◆ Load()

◆ Read()

◆ Save()

◆ SetBackgroundData()

◆ SetInputCol()

◆ SetKernelWidth()

◆ SetMetricsCol()

◆ SetModel()

◆ SetNumSamples()

◆ SetOutputCol()

◆ SetRegularization()

◆ SetTargetClasses()

◆ SetTargetClassesCol()

◆ SetTargetCol()