'Fit label binarizer
Parameters
y : array of shape [n_samples,] or [n_samples, n_classes]
Target values. The 2-d matrix should only contain 0 and 1,
represents multilabel classification.
Returns
self : returns an instance of self.'

def fit(self, y):

    self.y_type_ = type_of_target(y)
    if ('multioutput' in self.y_type_):
        raise ValueError('Multioutput    target    data    is    not    supported    with    label    binarization')
    if (_num_samples(y) == 0):
        raise ValueError(('y    has    0    samples:    %r' % y))
    self.sparse_input_ = sp.issparse(y)
    self.classes_ = unique_labels(y)
    return self
