Synapseml  0.10.0
Public Member Functions | Static Public Member Functions | List of all members
Synapse.ML.Explainers.TextSHAP Class Reference

TextSHAP implements TextSHAP More...

Inheritance diagram for Synapse.ML.Explainers.TextSHAP:
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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< TextSHAPRead ()
 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
uidAn 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
pathThe 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
pathThe path to save the object to

◆ SetInfWeight()

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

Sets value for infWeight

Parameters
valueThe 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
valueinput column name
Returns
New TextSHAP object

◆ SetMetricsCol()

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

Sets value for metricsCol

Parameters
valueColumn name for fitting metrics
Returns
New TextSHAP object

◆ SetModel()

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

Sets value for model

Parameters
valueThe model to be interpreted.
Returns
New TextSHAP object

◆ SetNumSamples()

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

Sets value for numSamples

Parameters
valueNumber of samples to generate.
Returns
New TextSHAP object

◆ SetOutputCol()

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

Sets value for outputCol

Parameters
valueoutput column name
Returns
New TextSHAP object

◆ SetTargetClasses()

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

Sets value for targetClasses

Parameters
valueThe 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
valueThe 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
valueThe 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
valueThe column holding the tokens
Returns
New TextSHAP object

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