def __init__(
        self,
        prob: float = 0.3,
        norm: int = 2,
        lamb: float = 0.5,
        solver: str = "L-BFGS-B",
        max_iter: int = 10,
        clip_values: "CLIP_VALUES_TYPE" | None = None,
        apply_fit: bool = False,
        apply_predict: bool = True,
        verbose: bool = False,
    ):
        """
        Create an instance of total variance minimization.

        :param prob: Probability of the Bernoulli distribution.
        :param norm: The norm (positive integer).
        :param lamb: The lambda parameter in the objective function.
        :param solver: Current support: `L-BFGS-B`, `CG`, `Newton-CG`.
        :param max_iter: Maximum number of iterations when performing optimization.
        :param clip_values: Tuple of the form `(min, max)` representing the minimum and maximum values allowed
               for features.
        :param apply_fit: True if applied during fitting/training.
        :param apply_predict: True if applied during predicting.
        :param verbose: Show progress bars.
        """
        super().__init__(is_fitted=True, apply_fit=apply_fit, apply_predict=apply_predict)
        self.prob = prob
        self.norm = norm
        self.lamb = lamb
        self.solver = solver
        self.max_iter = max_iter
        self.clip_values = clip_values
        self.verbose = verbose
        self._check_params()

        Create an instance of total variance minimization.

        :param prob: Probability of the Bernoulli distribution.
        :param norm: The norm (positive integer).
        :param lamb: The lambda parameter in the objective function.
        :param solver: Current support: `L-BFGS-B`, `CG`, `Newton-CG`.
        :param max_iter: Maximum number of iterations when performing optimization.
        :param clip_values: Tuple of the form `(min, max)` representing the minimum and maximum values allowed
               for features.
        :param apply_fit: True if applied during fitting/training.
        :param apply_predict: True if applied during predicting.
        :param verbose: Show progress bars.
        
art/defences/preprocessor/variance_minimization.py