include a constant or trend. If provided, these variables are
used as additional features in the regression operation.
y = check_array(y, ensure_2d=False, force_all_finite=False, copy=True, dtype=DTYPE)
// if exog was included, check the array...
if exogenous is not None:
exogenous = check_array(exogenous, ensure_2d=True, force_all_finite=False,
After Change
include a constant or trend. If provided, these variables are
used as additional features in the regression operation.
y = column_or_1d(check_array(y, ensure_2d=False, force_all_finite=False, copy=True, dtype=DTYPE))
n_samples = y.shape[0]
// if exog was included, check the array...
if exogenous is not None:
exogenous = check_array(exogenous, ensure_2d=True, force_all_finite=False,
copy=False, dtype=DTYPE)
// determine the CV args, if any
cv = self.out_of_sample_size
scoring = get_callable(self.scoring, VALID_SCORING)
cv = max(min(cv, n_samples), 0) // don"t allow negative, don"t allow > n_samples
def _fit_wrapper():
// these might change depending on which one
