Inheritance diagram for Synapse.ML.Explainers.TextSHAP:

Collaboration diagram for Synapse.ML.Explainers.TextSHAP:

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

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

TextSHAP	SetInfWeight (double value)
	Sets value for infWeight More...

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

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

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

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

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

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

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

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

TextSHAP	SetTokensCol (string value)
	Sets value for tokensCol More...

double	GetInfWeight ()
	Gets infWeight value More...

string	GetInputCol ()
	Gets inputCol 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...

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

string	GetTargetClassesCol ()
	Gets targetClassesCol value More...

string	GetTargetCol ()
	Gets targetCol value More...

string	GetTokensCol ()
	Gets tokensCol 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< TextSHAP >	Read ()
	Get the corresponding JavaMLReader instance. More...

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

Detailed Description

TextSHAP implements TextSHAP

Constructor & Destructor Documentation

◆ TextSHAP() [1/2]

Synapse.ML.Explainers.TextSHAP.TextSHAP ( )

inline

Creates a TextSHAP without any parameters.

◆ TextSHAP() [2/2]

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

inline

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

Parameters

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

Member Function Documentation

◆ GetInfWeight()

double Synapse.ML.Explainers.TextSHAP.GetInfWeight ( )

Gets infWeight value

Returns: infWeight: The double value to represent infinite weight. Default: 1E8.

◆ GetInputCol()

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

Gets inputCol value

Returns: inputCol: input column name

◆ GetMetricsCol()

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

Gets metricsCol value

Returns: metricsCol: Column name for fitting metrics

◆ GetModel()

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

inline

Gets model value

Returns: model: The model to be interpreted.

◆ GetNumSamples()

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

Gets numSamples value

Returns: numSamples: Number of samples to generate.

◆ GetOutputCol()

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

Gets outputCol value

Returns: outputCol: output column name

◆ GetTargetClasses()

int [] Synapse.ML.Explainers.TextSHAP.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.TextSHAP.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.TextSHAP.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

◆ GetTokensCol()

string Synapse.ML.Explainers.TextSHAP.GetTokensCol ( )

Gets tokensCol value

Returns: tokensCol: The column holding the tokens

◆ Load()

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

static

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

Parameters

path	The path the previous TextSHAP was saved to

Returns: New TextSHAP object, loaded from path.

◆ Read()

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

Get the corresponding JavaMLReader instance.

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

◆ Save()

void Synapse.ML.Explainers.TextSHAP.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

◆ SetInfWeight()

TextSHAP Synapse.ML.Explainers.TextSHAP.SetInfWeight ( double value )

Sets value for infWeight

Parameters

value The double value to represent infinite weight. Default: 1E8.

Returns: New TextSHAP object

◆ SetInputCol()

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

Sets value for inputCol

Parameters

value input column name

Returns: New TextSHAP object

◆ SetMetricsCol()

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

Sets value for metricsCol

Parameters

value Column name for fitting metrics

Returns: New TextSHAP object

◆ SetModel()

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

Sets value for model

Parameters

value The model to be interpreted.

Returns: New TextSHAP object

◆ SetNumSamples()

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

Sets value for numSamples

Parameters

value Number of samples to generate.

Returns: New TextSHAP object

◆ SetOutputCol()

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

Sets value for outputCol

Parameters

value output column name

Returns: New TextSHAP object

◆ SetTargetClasses()

TextSHAP Synapse.ML.Explainers.TextSHAP.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 TextSHAP object

◆ SetTargetClassesCol()

TextSHAP Synapse.ML.Explainers.TextSHAP.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 TextSHAP object

◆ SetTargetCol()

TextSHAP Synapse.ML.Explainers.TextSHAP.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 TextSHAP object

◆ SetTokensCol()

TextSHAP Synapse.ML.Explainers.TextSHAP.SetTokensCol ( string value )

Sets value for tokensCol

Parameters

value The column holding the tokens

Returns: New TextSHAP object

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

synapse/ml/explainers/TextSHAP.cs

Public Member Functions

Static Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ TextSHAP() [1/2]

◆ TextSHAP() [2/2]

Member Function Documentation

◆ GetInfWeight()

◆ GetInputCol()

◆ GetMetricsCol()

◆ GetModel()

◆ GetNumSamples()

◆ GetOutputCol()

◆ GetTargetClasses()

◆ GetTargetClassesCol()

◆ GetTargetCol()

◆ GetTokensCol()

◆ Load()

◆ Read()

◆ Save()

◆ SetInfWeight()

◆ SetInputCol()

◆ SetMetricsCol()

◆ SetModel()

◆ SetNumSamples()

◆ SetOutputCol()

◆ SetTargetClasses()

◆ SetTargetClassesCol()

◆ SetTargetCol()

◆ SetTokensCol()