Bases: QACategory
Defintion of the Fairness QACategory.
Source code in mlte/qa_category/fairness/fairness.py
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24 | class Fairness(QACategory):
"""
Defintion of the Fairness QACategory.
"""
def __init__(self, rationale: str):
"""Initialize a Fairness instance."""
super().__init__(
instance=self,
description="""
Fairness refers to the absence of biases in data and model inaccuracies that lead to models that treat individuals
or groups unfavorably on the basis of inherent or acquired characteristics (such as race, gender, disabilities,
or others). For ML models, this means ensuring similar model performance across specified subpopulations, groups,
or data.
""",
rationale=rationale,
)
|
__init__(rationale)
Initialize a Fairness instance.
Source code in mlte/qa_category/fairness/fairness.py
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24 | def __init__(self, rationale: str):
"""Initialize a Fairness instance."""
super().__init__(
instance=self,
description="""
Fairness refers to the absence of biases in data and model inaccuracies that lead to models that treat individuals
or groups unfavorably on the basis of inherent or acquired characteristics (such as race, gender, disabilities,
or others). For ML models, this means ensuring similar model performance across specified subpopulations, groups,
or data.
""",
rationale=rationale,
)
|