'Fit the EllipticEnvelope model with X.
Parameters
X : numpy array or sparse matrix of shape [n_samples, n_features]
Training data
y : (ignored)'

def fit(self, X, y=None):

    super(EllipticEnvelope, self).fit(X)
    self.threshold_ = sp.stats.scoreatpercentile(self.dist_, (100.0 * (1.0 - self.contamination)))
    return self
