def fit(self, X, y=None):
    '\n\n        Args:\n            X (2D array-like): An object suitable for FIS.batch_predict.\n            y (1D array-like): An array with true values. If None, but X is a DataFrame, the values are extracted from\n                               there.\n\n        Returns:\n\n        '
    if ((y is None) and (pd is not None) and isinstance(X, pd.DataFrame)):
        y = X[self.fis.target.name]
    self.cv.fit(X, y)
    self.best_params_ = self.cv.best_params_
    self.results = self.cv.cv_results_
    self.tuned_fis_ = _set_vars(self.fis, self.cv.best_params_)
Args:
    X (2D array-like): An object suitable for FIS.batch_predict.
    y (1D array-like): An array with true values. If None, but X is a DataFrame, the values are extracted from
                       there.

Returns:
def fit(self, X, y=None):
    '\n\n        Args:\n            X (2D array-like): An object suitable for FIS.batch_predict.\n            y (1D array-like): An array with true values. If None, but X is a DataFrame, the values are extracted from\n                               there.\n\n        Returns:\n\n        '
    if ((y is None) and (pd is not None) and isinstance(X, pd.DataFrame)):
        y = X[self.fis.target.name]
    self.cv.fit(X, y)
    self.best_params_ = self.cv.best_params_
    self.results = self.cv.cv_results_
    self.tuned_fis_ = _set_vars(self.fis, self.cv.best_params_)