TextSHAP implements TextSHAP
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◆ TextSHAP() [1/2]
Synapse.ML.Explainers.TextSHAP.TextSHAP |
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Creates a TextSHAP without any parameters.
◆ TextSHAP() [2/2]
Synapse.ML.Explainers.TextSHAP.TextSHAP |
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string |
uid | ) |
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Creates a TextSHAP with a UID that is used to give the TextSHAP a unique ID.
- Parameters
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uid | An immutable unique ID for the object and its derivatives. |
◆ GetInfWeight()
double Synapse.ML.Explainers.TextSHAP.GetInfWeight |
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Gets infWeight value
- Returns
- infWeight: The double value to represent infinite weight. Default: 1E8.
◆ GetInputCol()
string Synapse.ML.Explainers.TextSHAP.GetInputCol |
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Gets inputCol value
- Returns
- inputCol: input column name
◆ GetMetricsCol()
string Synapse.ML.Explainers.TextSHAP.GetMetricsCol |
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Gets metricsCol value
- Returns
- metricsCol: Column name for fitting metrics
◆ GetModel()
JavaTransformer Synapse.ML.Explainers.TextSHAP.GetModel |
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Gets model value
- Returns
- model: The model to be interpreted.
◆ GetNumSamples()
int Synapse.ML.Explainers.TextSHAP.GetNumSamples |
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Gets numSamples value
- Returns
- numSamples: Number of samples to generate.
◆ GetOutputCol()
string Synapse.ML.Explainers.TextSHAP.GetOutputCol |
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Gets outputCol value
- Returns
- outputCol: output column name
◆ GetTargetClasses()
int [] Synapse.ML.Explainers.TextSHAP.GetTargetClasses |
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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 |
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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 |
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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 |
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Gets tokensCol value
- Returns
- tokensCol: The column holding the tokens
◆ Load()
static TextSHAP Synapse.ML.Explainers.TextSHAP.Load |
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string |
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◆ Read()
JavaMLReader<TextSHAP> Synapse.ML.Explainers.TextSHAP.Read |
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Get the corresponding JavaMLReader instance.
- Returns
- an JavaMLReader<TextSHAP> instance for this ML instance.
◆ Save()
void Synapse.ML.Explainers.TextSHAP.Save |
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string |
path | ) |
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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
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path | The path to save the object to |
◆ SetInfWeight()
TextSHAP Synapse.ML.Explainers.TextSHAP.SetInfWeight |
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double |
value | ) |
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Sets value for infWeight
- Parameters
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value | The double value to represent infinite weight. Default: 1E8. |
- Returns
- New TextSHAP object
◆ SetInputCol()
TextSHAP Synapse.ML.Explainers.TextSHAP.SetInputCol |
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string |
value | ) |
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Sets value for inputCol
- Parameters
-
- Returns
- New TextSHAP object
◆ SetMetricsCol()
TextSHAP Synapse.ML.Explainers.TextSHAP.SetMetricsCol |
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string |
value | ) |
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Sets value for metricsCol
- Parameters
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value | Column name for fitting metrics |
- Returns
- New TextSHAP object
◆ SetModel()
TextSHAP Synapse.ML.Explainers.TextSHAP.SetModel |
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JavaTransformer |
value | ) |
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Sets value for model
- Parameters
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value | The model to be interpreted. |
- Returns
- New TextSHAP object
◆ SetNumSamples()
TextSHAP Synapse.ML.Explainers.TextSHAP.SetNumSamples |
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int |
value | ) |
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Sets value for numSamples
- Parameters
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value | Number of samples to generate. |
- Returns
- New TextSHAP object
◆ SetOutputCol()
TextSHAP Synapse.ML.Explainers.TextSHAP.SetOutputCol |
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string |
value | ) |
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Sets value for outputCol
- Parameters
-
- Returns
- New TextSHAP object
◆ SetTargetClasses()
TextSHAP Synapse.ML.Explainers.TextSHAP.SetTargetClasses |
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int[] |
value | ) |
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Sets value for targetClasses
- Parameters
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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 |
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string |
value | ) |
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Sets value for targetClassesCol
- Parameters
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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 |
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string |
value | ) |
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Sets value for targetCol
- Parameters
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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 |
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string |
value | ) |
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Sets value for tokensCol
- Parameters
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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