def cluster_meanshift(data, bandwidth=None, bin_seeding=False, **kwargs):
if bandwidth is None:<EOL><INDENT>bandwidth = cl.estimate_bandwidth(data)<EOL><DEDENT>ms = cl.MeanShift(bandwidth=bandwidth, bin_seeding=bin_seeding, **kwargs)<EOL>ms.fit(data)<EOL>labels = ms.labels_<EOL>return labels, [np.nan]<EOL>
Identify clusters using Meanshift algorithm.

Parameters
----------
data : array_like
    array of size [n_samples, n_features].
bandwidth : float or None
    If None, bandwidth is estimated automatically using
    sklean.cluster.estimate_bandwidth
bin_seeding : bool
    Setting this option to True will speed up the algorithm.
    See sklearn documentation for full description.

Returns
-------
dict
    boolean array for each identified cluster.