olpy/classifiers/cw.py
def _setup(self, X: np.ndarray):
        """Initializes the values for the model' parameters.

        Based on the data in argument, this method initializes 
        the parameters `sigma`, `phi`, `psi` and `x_i`.

        Args:
            X (:obj:`numpy.ndarray`): Input data with n rows and
                m columns

        Returns:
            None
        """
        self._sigma = self._a * np.eye(X.shape[1])
        self._phi = norm.ppf(self._eta)
        self._psi = 1 + (self._phi ** 2) / 2
        self._xi = 1 + self._phi ** 2
Initializes the values for the model' parameters.

        Based on the data in argument, this method initializes 
        the parameters `sigma`, `phi`, `psi` and `x_i`.

        Args:
            X (:obj:`numpy.ndarray`): Input data with n rows and
                m columns

        Returns:
            None
        
Initializes the values for the model' parameters.
Initializes the values for the model ' parameters .
def _setup(self, X: np.ndarray):
        self._sigma = self._a * np.eye(X.shape[1])
        self._phi = norm.ppf(self._eta)
        self._psi = 1 + (self._phi ** 2) / 2
        self._xi = 1 + self._phi ** 2
def _setup ( self , X : np . ndarray ) : self . _sigma = self . _a * np . eye ( X . shape [ 1 ] ) self . _phi = norm . ppf ( self . _eta ) self . _psi = 1 + ( self . _phi ** 2 ) / 2 self . _xi = 1 + self . _phi ** 2
Initializes the values for the model' parameters.
Initializes the values for the model ' parameters .
"""Initializes the values for the model' parameters.

        Based on the data in argument, this method initializes 
        the parameters `sigma`, `phi`, `psi` and `x_i`.

        Args:
            X (:obj:`numpy.ndarray`): Input data with n rows and
                m columns

        Returns:
            None
        """
None
self
X
np.ndarray
X (
`numpy.ndarray`): Input data with n rows and
m columns
` numpy . ndarray ` ) : Input data with n rows and m columns