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CounterfactualDetectionResult

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CounterfactualDetectionResult(
   concept_results: List[CounterfactualConceptResult]
)

The result of a counterfactual bias detection run.

Attributes

  • concept_results : A list of CounterfactualConceptResult objects.

Methods:

.save

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.save(
   path: str
)

Save the detection result to a file.

Load again by

from biaslyze.utils import load_results

results = load_results(path)

Args

  • path (str) : The path to save the result to.

Raises

  • ValueError : If the path is not valid.

.report

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.report()

Show an overview of the results.

Details: For each concept, the maximum mean and maximum standard deviation of the counterfactual scores is shown.

.dashboard

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.dashboard(
   num_keywords: int = 10, port: int = 8090
)

Start a dash dashboard with interactive box plots.

Args

  • num_keywords : The number of keywords per concept to show in the dashboard.
  • port : The port to run the dashboard on.

CounterfactualConceptResult

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CounterfactualConceptResult(
   concept: str, scores: pd.DataFrame, omitted_keywords: List[str],
   counterfactual_samples: Optional[List[CounterfactualSample]] = None
)

The result of a counterfactual bias detection run for a single concept.

Attributes

  • concept : The concept for which the result was calculated.
  • scores : The scores for the different keywords.
  • omitted_keywords : The keywords that were omitted from the analysis.
  • counterfactual_samples : The counterfactual samples that were generated.

CounterfactualSample

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CounterfactualSample(
   text: str, orig_keyword: str, keyword: str, concept: str,
   tokenized: TextRepresentation, score: Optional[float] = None,
   label: Optional[int|str] = None, source_text: Optional[str] = None
)

A sample for counterfactual bias detection.

Attributes

  • text : The original text.
  • orig_keyword : The original keyword.
  • keyword : The keyword that replaced the original keyword.
  • concept : The concept that was detected in the text.
  • tokenized : The tokenized text in spacy representation.
  • score : The counterfactual score of the sample.
  • label : The label of the original text.
  • source_text : The source text from which the text was derived.