def _prepare(self, X):
X = vstack([X, sqrt(self.c) * self.R])
estimator = TikhonovPseudoInv(X,
self.nPenalties,
intercept=self._intercept)
transforms = TransformList()
return estimator, transforms
def __init__(self, models, transforms=None, stats=None, algorithm=None):
self._models = models
if transforms is None:
self._transforms = TransformList()
else:
self._transforms = transforms
self._stats = stats
self._algorithm = algorithm
def _prepare(self, X):
if self._intercept:
X = AddConstant().transform(X)
estimator = PseudoInv(X)
transforms = TransformList()
return estimator, transforms
