tabular/src/autogluon/tabular/task/tabular_prediction/predictor.py
def positive_class(self):
        """
        Returns the positive class name in binary classification. Useful for computing metrics such as F1 which require a positive and negative class.
        In binary classification, `predictor.predict_proba()` returns the estimated probability that each row belongs to the positive class.
        Will print a warning and return None if called when `predictor.problem_type != 'binary'`.

        Returns
        -------
        The positive class name in binary classification or None if the problem is not binary classification.
        """
        if self.problem_type != BINARY:
            logger.warning(f"Warning: Attempted to retrieve positive class label in a non-binary problem. Positive class labels only exist in binary classification. Returning None instead. self.problem_type is '{self.problem_type}' but positive_class only exists for '{BINARY}'.")
            return None
        return self._learner.label_cleaner.cat_mappings_dependent_var[1]

        Returns the positive class name in binary classification. Useful for computing metrics such as F1 which require a positive and negative class.
        In binary classification, `predictor.predict_proba()` returns the estimated probability that each row belongs to the positive class.
        Will print a warning and return None if called when `predictor.problem_type != 'binary'`.

        Returns
        -------
        The positive class name in binary classification or None if the problem is not binary classification.
        
Returns the positive class name in binary classification. Useful for computing metrics such as F1 which require a positive and negative class.
In binary classification, `predictor.predict_proba()` returns the estimated probability that each row belongs to the positive class.
Will print a warning and return None if called when `predictor.problem_type != 'binary'`.

Returns

The positive class name in binary classification or None if the problem is not binary classification.
Returns the positive class name in binary classification . Useful for computing metrics such as F1 which require a positive and negative class . In binary classification ` predictor . predict_proba () ` returns the estimated probability that each row belongs to the positive class . Will print a warning and return None if called when ` predictor . problem_type ! = ' binary ' ` . Returns The positive class name in binary classification or None if the problem is not binary classification .
def positive_class(self):
        if self.problem_type != BINARY:
            logger.warning(f"Warning: Attempted to retrieve positive class label in a non-binary problem. Positive class labels only exist in binary classification. Returning None instead. self.problem_type is '{self.problem_type}' but positive_class only exists for '{BINARY}'.")
            return None
        return self._learner.label_cleaner.cat_mappings_dependent_var[1]
def positive_class ( self ) : if self . problem_type != BINARY : logger . warning ( f"Warning: Attempted to retrieve positive class label in a non-binary problem. Positive class labels only exist in binary classification. Returning None instead. self.problem_type is '{self.problem_type}' but positive_class only exists for '{BINARY}'." ) return None return self . _learner . label_cleaner . cat_mappings_dependent_var [ 1 ]
Returns the positive class name in binary classification.
Returns the positive class name in binary classification .
"""
        Returns the positive class name in binary classification. Useful for computing metrics such as F1 which require a positive and negative class.
        In binary classification, `predictor.predict_proba()` returns the estimated probability that each row belongs to the positive class.
        Will print a warning and return None if called when `predictor.problem_type != 'binary'`.

        Returns
        -------
        The positive class name in binary classification or None if the problem is not binary classification.
        """
self