scikits.learn.cluster.MeanShift

class scikits.learn.cluster.MeanShift(bandwidth=None)

MeanShift clustering

Parameters :

bandwidth: float, optional :

Bandwith used in the RBF kernel If not set, the bandwidth is estimated. See clustering.estimate_bandwidth

Notes

Reference:

K. Funkunaga and L.D. Hosteler, “The Estimation of the Gradient of a Density Function, with Applications in Pattern Recognition”

The algorithmic complexity of the mean shift algorithm is O(T n^2) with n the number of samples and T the number of iterations. It is not adviced for a large number of samples.

Attributes

cluster_centers_: array, [n_clusters, n_features]	Coordinates of cluster centers
labels_:	Labels of each point

Methods

fit(X):

Compute MeanShift clustering

__init__(bandwidth=None)

fit(X, **params)

Compute MeanShift

Parameters :

X : array [n_samples, n_features]

Input points